Description Usage Arguments Details Value Author(s) References See Also Examples
Compute every step from solar angles to effective irradiance to calculate the performance of a grid connected PV system.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | prodGCPV(lat,
modeTrk='fixed',
modeRad='prom',
dataRad,
prev, prom, mapa, bd,bdI,
sample='hour',
keep.night=TRUE,
sunGeometry='michalsky',
corr, f,
betaLim=90, beta=abs(lat)-10, alfa=0,
iS=2, alb=0.2, horizBright=TRUE, HCPV=FALSE,
module=list(),
generator=list(),
inverter=list(),
effSys=list(),
modeShd='',
struct=list(),
distances=data.frame()
)
|
lat |
numeric, latitude (degrees) of the point of the Earth where calculations are needed. It is positive for locations above the Equator. |
modeTrk |
A character string, describing the tracking method
of the generator. See |
modeRad, dataRad, prom, mapa, bd, bdI |
Information about the source data of the
global irradiation. See |
prev |
Deprecated, |
sample, keep.night |
See |
sunGeometry |
|
corr, f |
See |
betaLim, beta, alfa, iS, alb, horizBright, HCPV |
See |
module |
list of numeric values with information about the PV module,
|
generator |
list of numeric values with information about the generator,
|
inverter |
list of numeric values with information about the DC/AC inverter,
|
effSys |
list of numeric values with information about the system losses,
|
modeShd, struct, distances |
See |
The calculation of the irradiance on the horizontal plane is
carried out with the function calcG0
. The transformation
to the inclined surface makes use of the fTheta
and
fInclin
functions inside the calcGef
function. The shadows are computed with calcShd
while the performance of the PV system is simulated with fProd
.
A ProdGCPV
object.
Oscar Perpiñán Lamigueiro
Perpiñán, O, Energía Solar Fotovoltaica, 2012. (http://procomun.wordpress.com/documentos/libroesf/)
Perpiñán, O. (2012), "solaR: Solar Radiation and Photovoltaic Systems with R", Journal of Statistical Software, 50(9), 1-32, http://www.jstatsoft.org/v50/i09/
fProd
,
calcGef
,
calcShd
,
calcG0
,
compare
,
compareLosses
,
mergesolaR
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 | library(lattice)
library(latticeExtra)
lat=37.2;
G0dm=c(2766, 3491, 4494, 5912, 6989, 7742, 7919, 7027, 5369, 3562, 2814,
2179)
Ta=c(10, 14.1, 15.6, 17.2, 19.3, 21.2, 28.4, 29.9, 24.3, 18.2, 17.2, 15.2)
prom=list(G0dm=G0dm, Ta=Ta)
###Comparison of different tracker methods
prodFixed<-prodGCPV(lat=lat,dataRad=prom, keep.night=FALSE)
prod2x<-prodGCPV(lat=lat, dataRad=prom, modeTrk='two', keep.night=FALSE)
prodHoriz<-prodGCPV(lat=lat,dataRad=prom, modeTrk='horiz', keep.night=FALSE)
##Comparison of yearly productivities
compare(prodFixed, prod2x, prodHoriz)
compareLosses(prodFixed, prod2x, prodHoriz)
##Comparison of power time series
ComparePac<-CBIND(two=as.zooI(prod2x)$Pac,
horiz=as.zooI(prodHoriz)$Pac,
fixed=as.zooI(prodFixed)$Pac)
AngSol=as.zooI(as(prodFixed, 'Sol'))
ComparePac=CBIND(AngSol, ComparePac)
mon=month(index(ComparePac))
xyplot(two+horiz+fixed~AzS|mon, data=ComparePac,
type='l', auto.key=list(space='right', lines=TRUE, points=FALSE),ylab='Pac')
###Use of modeRad='aguiar' and modeRad='prev'
prodAguiarFixed <- prodGCPV(lat=41,
modeRad='aguiar',
dataRad=G0dm,
keep.night=FALSE)
##We want to compare systems with different effective irradiance
##so we have to convert prodAguiarFixed to a 'G0' object.
G0Aguiar=as(prodAguiarFixed, 'G0')
prodAguiar2x<-prodGCPV(lat=41,modeTrk='two',modeRad='prev', dataRad=G0Aguiar)
prodAguiarHoriz<-prodGCPV(lat=41, modeTrk='horiz',modeRad='prev',
dataRad=G0Aguiar)
##Comparison of yearly values
compare(prodAguiarFixed, prodAguiar2x, prodAguiarHoriz)
compareLosses(prodAguiarFixed, prodAguiar2x, prodAguiarHoriz)
##Compare of daily productivities of each tracking system
compareYf <- mergesolaR(prodAguiarFixed, prodAguiar2x, prodAguiarHoriz)
xyplot(compareYf, superpose=TRUE,
ylab='kWh/kWp', main='Daily productivity', auto.key=list(space='right'))
###Shadows
#Two-axis trackers
struct2x=list(W=23.11, L=9.8, Nrow=2, Ncol=8)
dist2x=data.frame(Lew=40, Lns=30, H=0)
prod2xShd<-prodGCPV(lat=lat, dataRad=prom, modeTrk='two',
modeShd='area', struct=struct2x, distances=dist2x)
print(prod2xShd)
#Horizontal N-S tracker
structHoriz=list(L=4.83);
distHoriz=data.frame(Lew=structHoriz$L*4);
#Without Backtracking
prodHorizShd<-prodGCPV(lat=lat, dataRad=prom, sample='10 min',
modeTrk='horiz',
modeShd='area', betaLim=60,
distances=distHoriz,
struct=structHoriz)
print(prodHorizShd)
xyplot(r2d(Beta)~r2d(w),
data=prodHorizShd,
type='l',
main='Inclination angle of a horizontal axis tracker',
xlab=expression(omega (degrees)),
ylab=expression(beta (degrees)))
#With Backtracking
prodHorizBT<-prodGCPV(lat=lat, dataRad=prom, sample='10 min',
modeTrk='horiz',
modeShd='bt', betaLim=60,
distances=distHoriz,
struct=structHoriz)
print(prodHorizBT)
xyplot(r2d(Beta)~r2d(w),
data=prodHorizBT,
type='l',
main='Inclination angle of a horizontal axis tracker\n with backtracking',
xlab=expression(omega (degrees)),
ylab=expression(beta (degrees)))
compare(prodFixed, prod2x, prodHoriz, prod2xShd,
prodHorizShd, prodHorizBT)
compareLosses(prodFixed, prod2x, prodHoriz, prod2xShd,
prodHorizShd, prodHorizBT)
compareYf2 <- mergesolaR(prodFixed, prod2x, prodHoriz, prod2xShd,
prodHorizShd, prodHorizBT)
xyplot(compareYf2, superpose=TRUE,
ylab='kWh/kWp', main='Daily productivity', auto.key=list(space='right'))
|
Loading required package: zoo
Attaching package: 'zoo'
The following objects are masked from 'package:base':
as.Date, as.Date.numeric
Loading required package: lattice
Loading required package: latticeExtra
Loading required package: RColorBrewer
Time Zone set to UTC.
values ind name
1 1835.874 G0d prodFixed
2 1969.056 Gefd prodFixed
3 1506.453 Yf prodFixed
4 1835.874 G0d prod2x
5 2961.440 Gefd prod2x
6 2235.135 Yf prod2x
7 1835.874 G0d prodHoriz
8 2611.055 Gefd prodHoriz
9 1991.057 Yf prodHoriz
id values name
1 Shadows 0.00000000 prodFixed
2 AoI 0.05894223 prodFixed
3 Generator 0.08395355 prodFixed
4 DC 0.07377200 prodFixed
5 Inverter 0.07067482 prodFixed
6 AC 0.02972575 prodFixed
7 Shadows 0.00000000 prod2x
8 AoI 0.02799467 prod2x
9 Generator 0.10029902 prod2x
10 DC 0.07302875 prod2x
11 Inverter 0.06730043 prod2x
12 AC 0.02972575 prod2x
13 Shadows 0.00000000 prodHoriz
14 AoI 0.03532082 prodHoriz
15 Generator 0.09141181 prodHoriz
16 DC 0.07302953 prodHoriz
17 Inverter 0.06687441 prodHoriz
18 AC 0.02972575 prodHoriz
Warning message:
In checkG0Ta(file, maxmin = TRUE) :
Ambient temperature data is not available. A new column with a constant value has been added.
values ind name
1 1828.003 G0d prodAguiarFixed
2 2043.465 Gefd prodAguiarFixed
3 1493.369 Yf prodAguiarFixed
4 1828.003 G0d prodAguiar2x
5 3041.820 Gefd prodAguiar2x
6 2176.249 Yf prodAguiar2x
7 1828.003 G0d prodAguiarHoriz
8 2609.069 Gefd prodAguiarHoriz
9 1910.956 Yf prodAguiarHoriz
id values name
1 Shadows 0.00000000 prodAguiarFixed
2 AoI 0.05857205 prodAguiarFixed
3 Generator 0.12290041 prodAguiarFixed
4 DC 0.07444595 prodAguiarFixed
5 Inverter 0.07219901 prodAguiarFixed
6 AC 0.02972575 prodAguiarFixed
7 Shadows 0.00000000 prodAguiar2x
8 AoI 0.02866849 prodAguiar2x
9 Generator 0.14440690 prodAguiar2x
10 DC 0.07331438 prodAguiar2x
11 Inverter 0.07000469 prodAguiar2x
12 AC 0.02972575 prodAguiar2x
13 Shadows 0.00000000 prodAguiarHoriz
14 AoI 0.03837420 prodAguiarHoriz
15 Generator 0.12500959 prodAguiarHoriz
16 DC 0.07335673 prodAguiarHoriz
17 Inverter 0.06898944 prodAguiarHoriz
18 AC 0.02972575 prodAguiarHoriz
Object of class ProdGCPV
Source of meteorological information: prom-
Latitude of source: 37.2 degrees
Latitude for calculations: 37.2 degrees
Monthly averages:
Eac Edc Yf
Jan 2018 124.7215 138.0163 4.713739
Feb 2018 130.8745 144.7641 4.946286
Mar 2018 140.6345 155.5684 5.315159
Apr 2018 168.7025 186.5415 6.375966
May 2018 193.5004 213.9344 7.313180
Jun 2018 217.7306 240.7905 8.228937
Jul 2018 209.6867 231.9225 7.924927
Aug 2018 187.4227 207.2682 7.083478
Sep 2018 157.9723 174.7537 5.970425
Oct 2018 122.1468 135.0042 4.616432
Nov 2018 117.0166 129.3715 4.422539
Dec 2018 94.2313 104.0767 3.561390
Yearly values:
Eac Edc Yf
2018 56749.8 62756.63 2144.809
-----------------
Mode of tracking: two
Inclination limit: 90
-----------------
Generator:
Modules in series: 12
Modules in parallel: 11
Nominal power (kWp): 26.5
Object of class ProdGCPV
Source of meteorological information: prom-
Latitude of source: 37.2 degrees
Latitude for calculations: 37.2 degrees
Monthly averages:
Eac Edc Yf
Jan 2018 84.52913 93.38235 3.194705
Feb 2018 100.81835 111.37086 3.810342
Mar 2018 123.82359 136.79909 4.679805
Apr 2018 158.77609 175.50712 6.000804
May 2018 183.38794 202.87785 6.930988
Jun 2018 201.00146 222.48441 7.596675
Jul 2018 199.14413 220.39634 7.526479
Aug 2018 178.27067 197.19524 6.737585
Sep 2018 143.41431 158.45096 5.420219
Oct 2018 98.46622 108.77931 3.721445
Nov 2018 81.74756 90.35178 3.089578
Dec 2018 62.53328 69.36882 2.363391
Yearly values:
Eac Edc Yf
2018 49205.9 54414.98 1859.694
-----------------
Mode of tracking: horiz
Inclination limit: 60
-----------------
Generator:
Modules in series: 12
Modules in parallel: 11
Nominal power (kWp): 26.5
Object of class ProdGCPV
Source of meteorological information: prom-
Latitude of source: 37.2 degrees
Latitude for calculations: 37.2 degrees
Monthly averages:
Eac Edc Yf
Jan 2018 83.85541 92.66168 3.169242
Feb 2018 100.22090 110.69118 3.787762
Mar 2018 123.30126 136.19999 4.660064
Apr 2018 158.13641 174.82349 5.976628
May 2018 182.56563 201.91562 6.899909
Jun 2018 200.02618 221.35747 7.559815
Jul 2018 198.16629 219.30665 7.489522
Aug 2018 177.31047 196.08399 6.701295
Sep 2018 142.70996 157.69740 5.393599
Oct 2018 98.02980 108.31354 3.704951
Nov 2018 81.16504 89.72941 3.067562
Dec 2018 62.01912 68.77977 2.343959
Yearly values:
Eac Edc Yf
2018 48950 54128.68 1850.023
-----------------
Mode of tracking: horiz
Inclination limit: 60
-----------------
Generator:
Modules in series: 12
Modules in parallel: 11
Nominal power (kWp): 26.5
values ind name
1 1835.874 G0d prodFixed
2 1969.056 Gefd prodFixed
3 1506.453 Yf prodFixed
4 1835.874 G0d prod2x
5 2961.440 Gefd prod2x
6 2235.135 Yf prod2x
7 1835.874 G0d prodHoriz
8 2611.055 Gefd prodHoriz
9 1991.057 Yf prodHoriz
10 1835.874 G0d prod2xShd
11 2846.653 Gefd prod2xShd
12 2144.809 Yf prod2xShd
13 1835.874 G0d prodHorizShd
14 2446.167 Gefd prodHorizShd
15 1859.694 Yf prodHorizShd
16 1835.874 G0d prodHorizBT
17 2434.327 Gefd prodHorizBT
18 1850.023 Yf prodHorizBT
id values name
1 Shadows 0.00000000 prodFixed
2 AoI 0.05894223 prodFixed
3 Generator 0.08395355 prodFixed
4 DC 0.07377200 prodFixed
5 Inverter 0.07067482 prodFixed
6 AC 0.02972575 prodFixed
7 Shadows 0.00000000 prod2x
8 AoI 0.02799467 prod2x
9 Generator 0.10029902 prod2x
10 DC 0.07302875 prod2x
11 Inverter 0.06730043 prod2x
12 AC 0.02972575 prod2x
13 Shadows 0.00000000 prodHoriz
14 AoI 0.03532082 prodHoriz
15 Generator 0.09141181 prodHoriz
16 DC 0.07302953 prodHoriz
17 Inverter 0.06687441 prodHoriz
18 AC 0.02972575 prodHoriz
19 Shadows 0.03876072 prod2xShd
20 AoI 0.02799467 prod2xShd
21 Generator 0.10115812 prod2xShd
22 DC 0.07302902 prod2xShd
23 Inverter 0.06801210 prod2xShd
24 AC 0.02972575 prod2xShd
25 Shadows 0.04986709 prodHorizShd
26 AoI 0.03607461 prodHorizShd
27 Generator 0.09276341 prodHorizShd
28 DC 0.07330647 prodHorizShd
29 Inverter 0.06802516 prodHorizShd
30 AC 0.02972575 prodHorizShd
31 Shadows 0.00000000 prodHorizBT
32 AoI 0.04119810 prodHorizBT
33 Generator 0.09309111 prodHorizBT
34 DC 0.07336383 prodHorizBT
35 Inverter 0.06796822 prodHorizBT
36 AC 0.02972575 prodHorizBT
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