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\sayala\Documents\GitHub\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\sayala\Documents\GitHub\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 944.8593 116.66480 0.123473
1 0.601509 3.683183e-17 1.164490 1.142752 a9.1.a2.1.0.cellPVmodule.6457 a9.1.a2.1.0.cellPVmodule.2310 944.9186 108.86900 0.115215
2 0.430574 2.636503e-17 1.191136 1.169398 a9.1.a2.2.0.cellPVmodule.6457 a9.1.a2.2.0.cellPVmodule.2310 944.9760 101.76430 0.107690
3 0.259638 1.589824e-17 1.217781 1.196044 a9.1.a2.3.0.cellPVmodule.6457 a9.1.a2.3.0.cellPVmodule.2310 945.0333 97.60841 0.103286
4 0.088702 5.431448e-18 1.244427 1.222689 a9.1.a2.4.0.cellPVmodule.6457 a9.1.a2.4.0.cellPVmodule.2310 945.0907 96.65984 0.102276
5 -0.082233 -5.035345e-18 1.271072 1.249335 a9.1.a2.5.0.cellPVmodule.6457 a9.1.a2.5.0.cellPVmodule.2310 945.1480 95.05819 0.100575
6 -0.253169 -1.550214e-17 1.297718 1.275980 a9.1.a2.6.0.cellPVmodule.6457 a9.1.a2.6.0.cellPVmodule.2310 945.2054 96.83778 0.102451
7 -0.424105 -2.596893e-17 1.324363 1.302626 a9.1.a2.7.0.cellPVmodule.6457 a9.1.a2.7.0.cellPVmodule.2310 945.2628 102.45900 0.108392
8 -0.595040 -3.643572e-17 1.351009 1.329271 a9.1.a2.8.0.cellPVmodule.6457 a9.1.a2.8.0.cellPVmodule.2310 946.0780 105.59260 0.111611
9 -0.765976 -4.690252e-17 1.377654 1.355917 a9.1.a2.9.0.cellPVmodule.6457 a9.1.a2.9.0.cellPVmodule.2310 946.0906 111.11640 0.117448 
[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 944.7910 127.7906 0.135258
1 0.601509 3.683183e-17 1.164490 1.142752 a9.1.a2.1.0.cellPVmodule.6457 a9.1.a2.1.0.cellPVmodule.2310 944.8566 121.8282 0.128938
2 0.430574 2.636503e-17 1.191136 1.169398 a9.1.a2.2.0.cellPVmodule.6457 a9.1.a2.2.0.cellPVmodule.2310 944.9208 115.7133 0.122458
3 0.259638 1.589824e-17 1.217781 1.196044 a9.1.a2.3.0.cellPVmodule.6457 a9.1.a2.3.0.cellPVmodule.2310 944.9850 111.3911 0.117876
4 0.088702 5.431448e-18 1.244427 1.222689 a9.1.a2.4.0.cellPVmodule.6457 a9.1.a2.4.0.cellPVmodule.2310 945.0492 105.4847 0.111618
5 -0.082233 -5.035345e-18 1.271072 1.249335 a9.1.a2.5.0.cellPVmodule.6457 a9.1.a2.5.0.cellPVmodule.2310 945.4636 109.0423 0.115332
6 -0.253169 -1.550214e-17 1.297718 1.275980 a9.1.a2.6.0.cellPVmodule.6457 a9.1.a2.6.0.cellPVmodule.2310 945.4807 109.1814 0.115477
7 -0.424105 -2.596893e-17 1.324363 1.302626 a9.1.a2.7.0.cellPVmodule.6457 a9.1.a2.7.0.cellPVmodule.2310 945.4962 110.7382 0.117122
8 -0.595040 -3.643572e-17 1.351009 1.329271 a9.1.a2.8.0.cellPVmodule.6457 a9.1.a2.8.0.cellPVmodule.2310 945.5118 114.4013 0.120994
9 -0.765976 -4.690252e-17 1.377654 1.355917 a9.1.a2.9.0.cellPVmodule.6457 a9.1.a2.9.0.cellPVmodule.2310 945.5274 118.3969 0.125218

Improvement in Rear Irradiance#

[17]:

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

[17]:

10.8

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 579.5359 27.76016 0.047901
1 0.320937 1.965169e-17 0.723122 0.712122 a9.1.a2.1.0.cellPVmodule.6457 a9.1.a2.1.0.cellPVmodule.2310 583.5565 26.74639 0.045833
2 0.234436 1.435510e-17 0.872944 0.861944 a9.1.a2.2.0.cellPVmodule.6457 a9.1.a2.2.0.cellPVmodule.2310 591.8787 26.89933 0.045447
3 0.147936 9.058500e-18 1.022766 1.011766 a9.1.a2.3.0.cellPVmodule.6457 a9.1.a2.3.0.cellPVmodule.2310 596.0308 27.00327 0.045305
4 0.061437 3.761903e-18 1.172589 1.161589 a9.1.a2.4.0.cellPVmodule.6457 a9.1.a2.4.0.cellPVmodule.2310 601.7504 27.09849 0.045033
5 -0.025063 -1.534695e-18 1.322411 1.311411 a9.1.a2.5.0.cellPVmodule.6457 a9.1.a2.5.0.cellPVmodule.2310 605.6486 26.53406 0.043811
6 -0.111563 -6.831292e-18 1.472234 1.461234 a9.1.a2.6.0.cellPVmodule.6457 a9.1.a2.6.0.cellPVmodule.2310 612.0669 27.14638 0.044352
7 -0.198064 -1.212789e-17 1.622056 1.611056 a9.1.a2.7.0.cellPVmodule.6457 a9.1.a2.7.0.cellPVmodule.2310 615.5109 27.55200 0.044763
8 -0.284564 -1.742449e-17 1.771878 1.760878 a9.1.a2.8.0.cellPVmodule.6457 a9.1.a2.8.0.cellPVmodule.2310 619.5745 28.53212 0.046051
9 -0.371063 -2.272108e-17 1.921701 1.910701 a9.1.a2.9.0.cellPVmodule.6457 a9.1.a2.9.0.cellPVmodule.2310 622.4969 29.04205 0.046654 
[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 579.1415 20.88081 0.036055
1 0.320937 1.965169e-17 0.723122 0.712122 a9.1.a2.1.0.cellPVmodule.6457 a9.1.a2.1.0.cellPVmodule.2310 582.8452 21.34479 0.036622
2 0.234436 1.435510e-17 0.872944 0.861944 a9.1.a2.2.0.cellPVmodule.6457 a9.1.a2.2.0.cellPVmodule.2310 591.8007 20.74030 0.035046
3 0.147936 9.058500e-18 1.022766 1.011766 a9.1.a2.3.0.cellPVmodule.6457 a9.1.a2.3.0.cellPVmodule.2310 595.6917 21.40979 0.035941
4 0.061437 3.761903e-18 1.172589 1.161589 a9.1.a2.4.0.cellPVmodule.6457 a9.1.a2.4.0.cellPVmodule.2310 602.5026 22.87528 0.037967
5 -0.025063 -1.534695e-18 1.322411 1.311411 a9.1.a2.5.0.cellPVmodule.6457 a9.1.a2.5.0.cellPVmodule.2310 606.3221 23.75233 0.039174
6 -0.111563 -6.831292e-18 1.472234 1.461234 a9.1.a2.6.0.cellPVmodule.6457 a9.1.a2.6.0.cellPVmodule.2310 612.8148 24.00990 0.039180
7 -0.198064 -1.212789e-17 1.622056 1.611056 a9.1.a2.7.0.cellPVmodule.6457 a9.1.a2.7.0.cellPVmodule.2310 616.6312 25.03161 0.040594
8 -0.284564 -1.742449e-17 1.771878 1.760878 a9.1.a2.8.0.cellPVmodule.6457 a9.1.a2.8.0.cellPVmodule.2310 619.6736 26.37031 0.042555
9 -0.371063 -2.272108e-17 1.921701 1.910701 a9.1.a2.9.0.cellPVmodule.6457 a9.1.a2.9.0.cellPVmodule.2310 622.9435 27.44040 0.044050 
[21]:

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

[21]:

17.3

[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())

17.3
39.4
33.5
22.8
8.7
9.7
10.0
9.7
17.2
32.3
37.8
39.9

[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:  20.1

[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

[27]:

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...

[28]:

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')

[28]:

Text(0.5, 0, 'Hour')
../_images/tutorials_14_-_Cement_Racking_Albedo_Improvements_35_1.png

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12 - AgriPV Clearance Height Evaluation