[ ]:

# This information helps with debugging and getting support :)
import sys, platform
import pandas as pd
import bifacial_radiance as br
print("Working on a ", platform.system(), platform.release())
print("Python version ", sys.version)
print("Pandas version ", pd.__version__)
print("bifacial_radiance version ", br.__version__)

14 - Cement Racking Albedo Improvements#

This journal creates a paver underneath the single-axis trackers, and evaluates the improvement for one day – June 17th with and without the pavers for a location in Davis, CA.

Paver

Measurements: Paver

[1]:

import os
from pathlib import Path
import pandas as pd

testfolder = str(Path().resolve().parent.parent / 'bifacial_radiance' / 'TEMP' / 'Tutorial_14')
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\mprillim\sam_dev\bifacial_radiance\bifacial_radiance\TEMP\Tutorial_14

[2]:

from bifacial_radiance import *
import numpy as np

[3]:

simulationname = 'tutorial_14'

#Location:
lat = 38.5449 # Davis, CA
lon = -121.7405 # Davis, CA
# MakeModule Parameters
moduletype='test-module'
numpanels = 1  # AgriPV site has 3 modules along the y direction (N-S since we are facing it to the south) .
x = 0.95
y = 1.838
xgap = 0.02# Leaving 2 centimeters between modules on x direction
ygap = 0.0 # 1 - up
zgap = 0.06 # gap between modules and torquetube.

# Other default values:

# TorqueTube Parameters
axisofrotationTorqueTube=True
torqueTube = False
cellLevelModule = True

numcellsx = 6
numcellsy = 10
xcell = 0.156
ycell = 0.158
xcellgap = 0.015
ycellgap = 0.015

sensorsy = numcellsy   # one sensor per cell

cellLevelModuleParams = {'numcellsx': numcellsx, 'numcellsy':numcellsy,
                         'xcell': xcell, 'ycell': ycell, 'xcellgap': xcellgap, 'ycellgap': ycellgap}

# SceneDict Parameters
gcr = 0.33 # m
albedo = 0.2  #'grass'     # ground albedo
hub_height = 1.237 # m
nMods = 20 # six modules per row.
nRows = 3  # 3 row

azimuth_ang = 90 # Facing east


demo = RadianceObj(simulationname,path = testfolder)  # Create a RadianceObj 'object'
demo.setGround(albedo) #
epwfile = demo.getEPW(lat, lon)
metdata = demo.readWeatherFile(epwfile, coerce_year=2021) # read in the EPW weather data from above
mymodule=demo.makeModule(name=moduletype,x=x,y=y,numpanels = numpanels, xgap=xgap, ygap=ygap)
mymodule.addCellModule(numcellsx=numcellsx, numcellsy=numcellsy,
                       xcell=xcell, ycell=ycell, xcellgap=xcellgap, ycellgap=ycellgap)

path = C:\Users\mprillim\sam_dev\bifacial_radiance\bifacial_radiance\TEMP\Tutorial_14
Loading albedo, 1 value(s), 0.200 avg
1 nonzero albedo values.
Getting weather file: USA_CA_Sacramento.Metro.AP.724839_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

Module Name: test-module
Module test-module updated in module.json
Pre-existing .rad file objects\test-module.rad will be overwritten

Module was shifted by 0.078 in X to avoid sensors on air
This is a Cell-Level detailed module with Packaging Factor of 0.85 %
Module test-module updated in module.json
Pre-existing .rad file objects\test-module.rad will be overwritten


[4]:

description = 'Sherman Williams "Chantilly White" acrylic paint'
materialpav = 'sw_chantillywhite'
Rrefl = 0.5
Grefl = 0.5
Brefl = 0.5
demo.addMaterial(material=materialpav, Rrefl=Rrefl, Grefl=Grefl, Brefl=Brefl, comment=description)

Material exists, overwriting...

Added material sw_chantillywhite to file ground.rad

Simulation without Pavers#

[5]:

timeindex = metdata.datetime.index(pd.to_datetime('2021-06-17 12:0:0 -8'))  # Davis, CA is TZ -8
demo.gendaylit(timeindex)

tilt = demo.getSingleTimestampTrackerAngle(metdata, timeindex=timeindex, gcr=gcr,
                                   azimuth=180, axis_tilt=0,
                                   limit_angle=60, backtrack=True)
# create a scene with all the variables
sceneDict = {'tilt':tilt,'gcr': gcr,'hub_height':hub_height,'azimuth':azimuth_ang, 'module_type':moduletype, 'nMods': nMods, 'nRows': nRows}
scene = demo.makeScene(module=mymodule, sceneDict=sceneDict) #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 fil|es into a .oct file.

Created tutorial_14.oct

[6]:

analysis = AnalysisObj(octfile, demo.name)  # return an analysis object including the scan dimensions for back irradiance
frontscan, backscan = analysis.moduleAnalysis(scene, sensorsy=sensorsy)
analysis.analysis(octfile, simulationname+"_noPavers", frontscan, backscan)  # compare the back vs front irradiance
print("Simulation without Pavers Finished")

Linescan in process: tutorial_14_noPavers_Front
Linescan in process: tutorial_14_noPavers_Back
Saved: results\irr_tutorial_14_noPavers.csv
Simulation without Pavers Finished

Looping on the day#

[7]:

j=0
starttimeindex = metdata.datetime.index(pd.to_datetime('2021-06-17 7:0:0 -8'))
endtimeindex = metdata.datetime.index(pd.to_datetime('2021-06-17 19:0:0 -8'))
for timess in range (starttimeindex, endtimeindex):
    j+=1
    demo.gendaylit(timess)
    tilt = demo.getSingleTimestampTrackerAngle(metdata, timeindex=timess, gcr=gcr,
                                       azimuth=180, axis_tilt=0,
                                       limit_angle=60, backtrack=True)
    # create a scene with all the variables
    sceneDict = {'tilt':tilt,'gcr': gcr,'hub_height':hub_height,'azimuth':azimuth_ang, 'module_type':moduletype, 'nMods': nMods, 'nRows': nRows}
    scene = demo.makeScene(module=mymodule, sceneDict=sceneDict) #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 fil|es into a .oct file
    frontscan, backscan = analysis.moduleAnalysis(scene, sensorsy=sensorsy)
    analysis.analysis(octfile, simulationname+"_noPavers_"+str(j), frontscan, backscan)  # compare the back vs front irradiance

Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_1_Front
Linescan in process: tutorial_14_noPavers_1_Back
Saved: results\irr_tutorial_14_noPavers_1.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_2_Front
Linescan in process: tutorial_14_noPavers_2_Back
Saved: results\irr_tutorial_14_noPavers_2.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_3_Front
Linescan in process: tutorial_14_noPavers_3_Back
Saved: results\irr_tutorial_14_noPavers_3.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_4_Front
Linescan in process: tutorial_14_noPavers_4_Back
Saved: results\irr_tutorial_14_noPavers_4.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_5_Front
Linescan in process: tutorial_14_noPavers_5_Back
Saved: results\irr_tutorial_14_noPavers_5.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_6_Front
Linescan in process: tutorial_14_noPavers_6_Back
Saved: results\irr_tutorial_14_noPavers_6.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_7_Front
Linescan in process: tutorial_14_noPavers_7_Back
Saved: results\irr_tutorial_14_noPavers_7.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_8_Front
Linescan in process: tutorial_14_noPavers_8_Back
Saved: results\irr_tutorial_14_noPavers_8.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_9_Front
Linescan in process: tutorial_14_noPavers_9_Back
Saved: results\irr_tutorial_14_noPavers_9.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_10_Front
Linescan in process: tutorial_14_noPavers_10_Back
Saved: results\irr_tutorial_14_noPavers_10.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_11_Front
Linescan in process: tutorial_14_noPavers_11_Back
Saved: results\irr_tutorial_14_noPavers_11.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_noPavers_12_Front
Linescan in process: tutorial_14_noPavers_12_Back
Saved: results\irr_tutorial_14_noPavers_12.csv

Simulation With Pavers#

[8]:

demo.gendaylit(timeindex)
tilt = demo.getSingleTimestampTrackerAngle(metdata, timeindex=timeindex, gcr=gcr,
                                   azimuth=180, axis_tilt=0,
                                   limit_angle=60, backtrack=True)
# create a scene with all the variables
sceneDict = {'tilt':tilt,'gcr': gcr,'hub_height':hub_height,'azimuth':azimuth_ang, 'module_type':moduletype, 'nMods': nMods, 'nRows': nRows}
scene = demo.makeScene(module=mymodule, sceneDict=sceneDict) #makeScene creates a .rad file with 20 modules per row, 7 rows.

[9]:

torquetubelength = demo.module.scenex*(nMods)
pitch = demo.module.sceney/gcr
startpitch = -pitch * (nRows-1)/2
p_w = 0.947 # m
p_h = 0.092 # m
p_w2 = 0.187 # m
p_h2 = 0.184 # m
offset_w1y = -(p_w/2)+(p_w2/2)
offset_w2y = (p_w/2)-(p_w2/2)

customObjects = []
for i in range (0, nRows):
    name='PAVER'+str(i)
    text='! genbox {} paver{} {} {} {} | xform -t {} {} 0 | xform -t {} 0 0'.format(materialpav, i,
                                    p_w, torquetubelength, p_h,
                                    -p_w/2, (-torquetubelength+demo.module.sceney)/2.0,
                                    startpitch+pitch*i)
    text += '\r\n! genbox {} paverS1{} {} {} {} | xform -t {} {} 0 | xform -t {} 0 0'.format(materialpav, i,
                                    p_w2, torquetubelength, p_h2,
                                    -p_w2/2+offset_w1y, (-torquetubelength+demo.module.sceney)/2.0,
                                    startpitch+pitch*i)
    text += '\r\n! genbox {} paverS2{} {} {} {} | xform -t {} {} 0 | xform -t {} 0 0'.format(materialpav, i,
                                    p_w2, torquetubelength, p_h2,
                                    -p_w2/2+offset_w2y, (-torquetubelength+demo.module.sceney)/2.0,
                                    startpitch+pitch*i)

    customObject = demo.makeCustomObject(name,text)
    customObjects.append(customObject)
    demo.appendtoScene(radfile=scene.radfiles, customObject=customObject, text="!xform -rz 0")


Custom Object Name objects\PAVER0.rad

Custom Object Name objects\PAVER1.rad

Custom Object Name objects\PAVER2.rad

[10]:

demo.makeOct()

Created tutorial_14.oct

[10]:

'tutorial_14.oct'

You can view the geometry generated in the terminal with:

rvu -vf views:nbsphinx-math:`front`.vp -e .01 -pe 0.01 -vp -5 -14 1 -vd 0 0.9946 -0.1040 tutorial_14.oct

[11]:


## 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 .01 -pe 0.01 -vp -5 -14 1 -vd 0 0.9946 -0.1040 tutorial_14.oct

[12]:

analysis = AnalysisObj(octfile, demo.name)  # return an analysis object including the scan dimensions for back irradiance
frontscan, backscan = analysis.moduleAnalysis(scene, sensorsy=sensorsy)
analysis.analysis(octfile, simulationname+"_WITHPavers", frontscan, backscan)  # compare the back vs front irradiance
print("Simulation WITH Pavers Finished")

Linescan in process: tutorial_14_WITHPavers_Front
Linescan in process: tutorial_14_WITHPavers_Back
Saved: results\irr_tutorial_14_WITHPavers.csv
Simulation WITH Pavers Finished

LOOP WITH PAVERS#

[13]:

j=0
for timess in range (starttimeindex, endtimeindex):
    j+=1
    demo.gendaylit(timess)
    tilt = demo.getSingleTimestampTrackerAngle(metdata, timeindex=timess, gcr=gcr,
                                       azimuth=180, axis_tilt=0,
                                       limit_angle=60, backtrack=True)
    # create a scene with all the variables
    sceneDict = {'tilt':tilt,'gcr': gcr,'hub_height':hub_height,'azimuth':azimuth_ang, 'module_type':moduletype, 'nMods': nMods, 'nRows': nRows}
    scene = demo.makeScene(mymodule, sceneDict=sceneDict) #makeScene creates a .rad file with 20 modules per row, 7 rows.
    # Appending Pavers here
    demo.appendtoScene(radfile=scene.radfiles, customObject=customObjects[0], text="!xform -rz 0")
    demo.appendtoScene(radfile=scene.radfiles, customObject=customObjects[1], text="!xform -rz 0")
    demo.appendtoScene(radfile=scene.radfiles, customObject=customObjects[2], text="!xform -rz 0")
    octfile = demo.makeOct(demo.getfilelist())  # makeOct combines all of the ground, sky and object fil|es into a .oct file
    frontscan, backscan = analysis.moduleAnalysis(scene, sensorsy=sensorsy)
    analysis.analysis(octfile, simulationname+"_WITHPavers_"+str(j), frontscan, backscan)  # compare the back vs front irradiance

Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_1_Front
Linescan in process: tutorial_14_WITHPavers_1_Back
Saved: results\irr_tutorial_14_WITHPavers_1.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_2_Front
Linescan in process: tutorial_14_WITHPavers_2_Back
Saved: results\irr_tutorial_14_WITHPavers_2.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_3_Front
Linescan in process: tutorial_14_WITHPavers_3_Back
Saved: results\irr_tutorial_14_WITHPavers_3.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_4_Front
Linescan in process: tutorial_14_WITHPavers_4_Back
Saved: results\irr_tutorial_14_WITHPavers_4.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_5_Front
Linescan in process: tutorial_14_WITHPavers_5_Back
Saved: results\irr_tutorial_14_WITHPavers_5.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_6_Front
Linescan in process: tutorial_14_WITHPavers_6_Back
Saved: results\irr_tutorial_14_WITHPavers_6.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_7_Front
Linescan in process: tutorial_14_WITHPavers_7_Back
Saved: results\irr_tutorial_14_WITHPavers_7.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_8_Front
Linescan in process: tutorial_14_WITHPavers_8_Back
Saved: results\irr_tutorial_14_WITHPavers_8.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_9_Front
Linescan in process: tutorial_14_WITHPavers_9_Back
Saved: results\irr_tutorial_14_WITHPavers_9.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_10_Front
Linescan in process: tutorial_14_WITHPavers_10_Back
Saved: results\irr_tutorial_14_WITHPavers_10.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_11_Front
Linescan in process: tutorial_14_WITHPavers_11_Back
Saved: results\irr_tutorial_14_WITHPavers_11.csv
Created tutorial_14.oct
Linescan in process: tutorial_14_WITHPavers_12_Front
Linescan in process: tutorial_14_WITHPavers_12_Back
Saved: results\irr_tutorial_14_WITHPavers_12.csv

RESULTS ANALYSIS NOON#

[14]:

df_0 = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_noPavers.csv'))
df_w = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_WITHPavers.csv'))

[15]:

df_0

[15]:
x y z rearZ mattype rearMat Wm2Front Wm2Back Back/FrontRatio
0 0.772445 4.729862e-17 1.137844 1.116107 a9.1.a2.0.0.cellPVmodule.6457 a9.1.a2.0.0.cellPVmodule.2310 946.8981 117.24230 0.123817
1 0.601509 3.683183e-17 1.164490 1.142752 a9.1.a2.1.0.cellPVmodule.6457 a9.1.a2.1.0.cellPVmodule.2310 946.8854 109.52570 0.115669
2 0.430574 2.636503e-17 1.191136 1.169398 a9.1.a2.2.0.cellPVmodule.6457 a9.1.a2.2.0.cellPVmodule.2310 946.8724 103.41390 0.109216
3 0.259638 1.589824e-17 1.217781 1.196044 a9.1.a2.3.0.cellPVmodule.6457 a9.1.a2.3.0.cellPVmodule.2310 946.8594 96.69959 0.102127
4 0.088702 5.431448e-18 1.244427 1.222689 a9.1.a2.4.0.cellPVmodule.6457 a9.1.a2.4.0.cellPVmodule.2310 946.8464 95.68785 0.101059
5 -0.082233 -5.035345e-18 1.271072 1.249335 a9.1.a2.5.0.cellPVmodule.6457 a9.1.a2.5.0.cellPVmodule.2310 946.8334 95.34497 0.100699
6 -0.253169 -1.550214e-17 1.297718 1.275980 a9.1.a2.6.0.cellPVmodule.6457 a9.1.a2.6.0.cellPVmodule.2310 947.6977 97.69968 0.103091
7 -0.424105 -2.596893e-17 1.324363 1.302626 a9.1.a2.7.0.cellPVmodule.6457 a9.1.a2.7.0.cellPVmodule.2310 947.7081 99.91356 0.105426
8 -0.595040 -3.643572e-17 1.351009 1.329271 a9.1.a2.8.0.cellPVmodule.6457 a9.1.a2.8.0.cellPVmodule.2310 947.7183 105.03310 0.110827
9 -0.765976 -4.690252e-17 1.377654 1.355917 a9.1.a2.9.0.cellPVmodule.6457 a9.1.a2.9.0.cellPVmodule.2310 947.7285 110.56770 0.116666 
[16]:

df_w

[16]:
x y z rearZ mattype rearMat Wm2Front Wm2Back Back/FrontRatio
0 0.772445 4.729862e-17 1.137844 1.116107 a9.1.a2.0.0.cellPVmodule.6457 a9.1.a2.0.0.cellPVmodule.2310 947.1658 125.5783 0.132583
1 0.601509 3.683183e-17 1.164490 1.142752 a9.1.a2.1.0.cellPVmodule.6457 a9.1.a2.1.0.cellPVmodule.2310 947.2082 119.3176 0.125968
2 0.430574 2.636503e-17 1.191136 1.169398 a9.1.a2.2.0.cellPVmodule.6457 a9.1.a2.2.0.cellPVmodule.2310 947.2504 114.9427 0.121343
3 0.259638 1.589824e-17 1.217781 1.196044 a9.1.a2.3.0.cellPVmodule.6457 a9.1.a2.3.0.cellPVmodule.2310 947.2926 110.5928 0.116746
4 0.088702 5.431448e-18 1.244427 1.222689 a9.1.a2.4.0.cellPVmodule.6457 a9.1.a2.4.0.cellPVmodule.2310 947.3348 112.6003 0.118860
5 -0.082233 -5.035345e-18 1.271072 1.249335 a9.1.a2.5.0.cellPVmodule.6457 a9.1.a2.5.0.cellPVmodule.2310 947.3168 111.2375 0.117424
6 -0.253169 -1.550214e-17 1.297718 1.275980 a9.1.a2.6.0.cellPVmodule.6457 a9.1.a2.6.0.cellPVmodule.2310 947.3401 108.4745 0.114504
7 -0.424105 -2.596893e-17 1.324363 1.302626 a9.1.a2.7.0.cellPVmodule.6457 a9.1.a2.7.0.cellPVmodule.2310 947.3632 109.8079 0.115909
8 -0.595040 -3.643572e-17 1.351009 1.329271 a9.1.a2.8.0.cellPVmodule.6457 a9.1.a2.8.0.cellPVmodule.2310 947.3864 110.1948 0.116314
9 -0.765976 -4.690252e-17 1.377654 1.355917 a9.1.a2.9.0.cellPVmodule.6457 a9.1.a2.9.0.cellPVmodule.2310 947.4094 114.2160 0.120556

Improvement in Rear Irradiance#

[17]:

round((df_w['Wm2Back'].mean()-df_0['Wm2Back'].mean())*100/df_0['Wm2Back'].mean(),1)

[17]:

10.3

RESULT ANALYSIS DAY#

[18]:

df_0 = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_noPavers_1.csv'))
df_w = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_WITHPavers_1.csv'))

[19]:

df_w

[19]:
x y z rearZ mattype rearMat Wm2Front Wm2Back Back/FrontRatio
0 0.407436 2.494829e-17 0.573299 0.562299 a9.1.a2.0.0.cellPVmodule.6457 a9.1.a2.0.0.cellPVmodule.2310 579.8174 27.50550 0.047438
1 0.320937 1.965169e-17 0.723122 0.712122 a9.1.a2.1.0.cellPVmodule.6457 a9.1.a2.1.0.cellPVmodule.2310 584.6388 27.33312 0.046752
2 0.234436 1.435510e-17 0.872944 0.861944 a9.1.a2.2.0.cellPVmodule.6457 a9.1.a2.2.0.cellPVmodule.2310 590.6924 27.54174 0.046626
3 0.147936 9.058500e-18 1.022766 1.011766 a9.1.a2.3.0.cellPVmodule.6457 a9.1.a2.3.0.cellPVmodule.2310 595.0419 26.06395 0.043802
4 0.061437 3.761903e-18 1.172589 1.161589 a9.1.a2.4.0.cellPVmodule.6457 a9.1.a2.4.0.cellPVmodule.2310 602.6788 26.42415 0.043844
5 -0.025063 -1.534695e-18 1.322411 1.311411 a9.1.a2.5.0.cellPVmodule.6457 a9.1.a2.5.0.cellPVmodule.2310 606.5762 26.13547 0.043087
6 -0.111563 -6.831292e-18 1.472234 1.461234 a9.1.a2.6.0.cellPVmodule.6457 a9.1.a2.6.0.cellPVmodule.2310 611.8985 26.60694 0.043483
7 -0.198064 -1.212789e-17 1.622056 1.611056 a9.1.a2.7.0.cellPVmodule.6457 a9.1.a2.7.0.cellPVmodule.2310 614.5859 26.76097 0.043543
8 -0.284564 -1.742449e-17 1.771878 1.760878 a9.1.a2.8.0.cellPVmodule.6457 a9.1.a2.8.0.cellPVmodule.2310 620.1961 27.76613 0.044770
9 -0.371063 -2.272108e-17 1.921701 1.910701 a9.1.a2.9.0.cellPVmodule.6457 a9.1.a2.9.0.cellPVmodule.2310 623.0681 27.96354 0.044880 
[20]:

df_0

[20]:
x y z rearZ mattype rearMat Wm2Front Wm2Back Back/FrontRatio
0 0.407436 2.494829e-17 0.573299 0.562299 a9.1.a2.0.0.cellPVmodule.6457 a9.1.a2.0.0.cellPVmodule.2310 581.4525 20.58496 0.035403
1 0.320937 1.965169e-17 0.723122 0.712122 a9.1.a2.1.0.cellPVmodule.6457 a9.1.a2.1.0.cellPVmodule.2310 584.9100 21.15021 0.036160
2 0.234436 1.435510e-17 0.872944 0.861944 a9.1.a2.2.0.cellPVmodule.6457 a9.1.a2.2.0.cellPVmodule.2310 592.2502 20.92997 0.035340
3 0.147936 9.058500e-18 1.022766 1.011766 a9.1.a2.3.0.cellPVmodule.6457 a9.1.a2.3.0.cellPVmodule.2310 596.4415 21.53978 0.036114
4 0.061437 3.761903e-18 1.172589 1.161589 a9.1.a2.4.0.cellPVmodule.6457 a9.1.a2.4.0.cellPVmodule.2310 603.3365 22.16977 0.036745
5 -0.025063 -1.534695e-18 1.322411 1.311411 a9.1.a2.5.0.cellPVmodule.6457 a9.1.a2.5.0.cellPVmodule.2310 606.5955 23.02444 0.037957
6 -0.111563 -6.831292e-18 1.472234 1.461234 a9.1.a2.6.0.cellPVmodule.6457 a9.1.a2.6.0.cellPVmodule.2310 613.5248 23.97887 0.039084
7 -0.198064 -1.212789e-17 1.622056 1.611056 a9.1.a2.7.0.cellPVmodule.6457 a9.1.a2.7.0.cellPVmodule.2310 617.3268 25.00761 0.040509
8 -0.284564 -1.742449e-17 1.771878 1.760878 a9.1.a2.8.0.cellPVmodule.6457 a9.1.a2.8.0.cellPVmodule.2310 621.6809 25.92181 0.041696
9 -0.371063 -2.272108e-17 1.921701 1.910701 a9.1.a2.9.0.cellPVmodule.6457 a9.1.a2.9.0.cellPVmodule.2310 624.8511 26.90095 0.043052 
[21]:

round((df_w['Wm2Back'].mean()-df_0['Wm2Back'].mean())*100/df_0['Wm2Back'].mean(),1)

[21]:

16.8

[22]:

average_back_d0=[]
average_back_dw=[]
average_front = []
hourly_rearirradiance_comparison = []

timessimulated = endtimeindex-starttimeindex

for i in range (1, timessimulated+1):
    df_0 = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_noPavers_'+str(i)+'.csv'))
    df_w = load.read1Result(os.path.join(testfolder, 'results', 'irr_tutorial_14_WITHPavers_'+str(i)+'.csv'))
    print(round((df_w['Wm2Back'].mean()-df_0['Wm2Back'].mean())*100/df_0['Wm2Back'].mean(),1))
    hourly_rearirradiance_comparison.append(round((df_w['Wm2Back'].mean()-df_0['Wm2Back'].mean())*100/df_0['Wm2Back'].mean(),1))
    average_back_d0.append(df_0['Wm2Back'].mean())
    average_back_dw.append(df_w['Wm2Back'].mean())
    average_front.append(df_0['Wm2Front'].mean())

16.8
40.7
34.7
23.3
9.3
10.6
10.3
9.7
18.4
32.3
36.5
40.4

[23]:

print("Increase in rear irradiance: ", round((sum(average_back_dw)-sum(average_back_d0))*100/sum(average_back_d0),1))

Increase in rear irradiance:  20.5

[24]:

print("BG no Pavers: ", round(sum(average_back_d0)*100/sum(average_front),1))
print("BG with Pavers: ", round(sum(average_back_dw)*100/sum(average_front),1))

BG no Pavers:  8.3
BG with Pavers:  10.0

[25]:

import matplotlib.pyplot as plt

#metdata.datetime[starttime].hour # 7
#metdata.datetime[endtimeindex].hour # 17
xax= [7, 8, 9, 10, 11, 12,13,14,15,16,17,18]  # Lazy way to get the x axis...

[26]:

plt.plot(xax,hourly_rearirradiance_comparison)
plt.ylabel('$\Delta$ in G$_{rear}$ [%] \n(G$_{rear-with}$ - G$_{rear-without}$ / G$_{rear-without}$)')
plt.xlabel('Hour')

[26]:

Text(0.5, 0, 'Hour')
../_images/tutorials_14_-_Cement_Racking_Albedo_Improvements_36_1.png
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