PinPV Fig 1

This journal shows how to use the Analysis function inside bifacialVF to call for PV Mismatch IV curve calculation and plotting for different irradiance values.

Estimating and parameterizing mismatch power loss in bifacial photovoltaic systems Chris Deline,Silvana Ayala Pelaez,Sara MacAlpine,Carlos Olalla First published: 06 March 2020 https://doi.org/10.1002/pip.3259Citations: 16

import bifacialvf
import pandas as pd

# SETUP:
City='Cairo'
WeatherFile = 'EGY_Cairo.Intl.Airport.623660_ETMY'
Latitude = 30.13
Longitude= 31.4
Timezone = 2
Tilt = 10
Azimuth = 180
GroundClearance = 0.15
RtR = 1.5
RowType = 'interior'
TransmissionFactor = 0.013
CellRows = 6
PVfrontSurface = 'glass'
PVbackSurface = 'glass'
Albedo = 0.62
Tracking = False
calculatePVMismatch = True
PortraitorLandscape = 'landscape'

# PVMismatch calculation
# BifacialVF front and rear irradiance values for June 21st. at 2 PM
frontGTIrow = [927.6982631, 928.4082993, 928.8050623, 931.0767397, 933.0536854, 933.8064969]
backGTIrow = [131.7201933, 47.90228722, 38.49283059, 54.58803934, 100.6857589, 194.5133033]

portraitorlandscape='landscape'
sensorsy=len(frontGTIrow)
debug=True
numcells=72
plotflag = True

stdpl, cellsx, cellsy = bifacialvf.analysis.setupforPVMismatch(portraitorlandscape=portraitorlandscape, sensorsy=sensorsy, numcells=numcells)

PowerAveraged, PowerDetailed, sunmatAveraged, sunmatDetailed = bifacialvf.analysis.calculateVFPVMismatch(stdpl=stdpl, cellsx=cellsx, cellsy=cellsy, sensorsy=sensorsy, frontGTIrow=frontGTIrow, backGTIrow=backGTIrow, bififactor=1.0, debug=debug, plotflag = plotflag)

print("Results: ", round(PowerAveraged,3), round(PowerDetailed,2))

print(portraitorlandscape, "Cellsx", cellsx, "Cellsy", cellsy)
print(pd.DataFrame(stdpl))
print(pd.DataFrame(sunmatAveraged).round(3))
pd.DataFrame(sunmatDetailed).round(3)

Results:  247.097 242.14
landscape Cellsx 12 Cellsy 6
   0   1   2   3   4   5   6   7   8   9   10  11
0   0   1   2   3   4   5   6   7   8   9  10  11
1  23  22  21  20  19  18  17  16  15  14  13  12
2  24  25  26  27  28  29  30  31  32  33  34  35
3  47  46  45  44  43  42  41  40  39  38  37  36
4  48  49  50  51  52  53  54  55  56  57  58  59
5  71  70  69  68  67  66  65  64  63  62  61  60
      0      1      2      3      4      5      6      7      8      9   \
0  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025   
1  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025   
2  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025   
3  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025   
4  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025   
5  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025  1.025   

      10     11  
0  1.025  1.025  
1  1.025  1.025  
2  1.025  1.025  
3  1.025  1.025  
4  1.025  1.025  
5  1.025  1.025  

	0	1	2	3	4	5	6	7	8	9	10	11
0	1.059	1.059	1.059	1.059	1.059	1.059	1.059	1.059	1.059	1.059	1.059	1.059
1	0.976	0.976	0.976	0.976	0.976	0.976	0.976	0.976	0.976	0.976	0.976	0.976
2	0.967	0.967	0.967	0.967	0.967	0.967	0.967	0.967	0.967	0.967	0.967	0.967
3	0.986	0.986	0.986	0.986	0.986	0.986	0.986	0.986	0.986	0.986	0.986	0.986
4	1.034	1.034	1.034	1.034	1.034	1.034	1.034	1.034	1.034	1.034	1.034	1.034
5	1.128	1.128	1.128	1.128	1.128	1.128	1.128	1.128	1.128	1.128	1.128	1.128