solaR (version 0.14)

optimSombra: Shadows calculation for a set of distances between elements of a PV grid connected plant.

Description

The optimum distance between trackers or static structures of a PV grid connected plant depends on two main factors: the ground cover ratio (defined as the ratio of the PV array area to the total ground area), and the productivity of the system including shadow losses. Therefore, the optimum separation may be the one which achieves the highest productivity with the highest ground cover ratio. However, this definition is not complete since the terrain characteristics and the costs of wiring or civil works could alter the decision. This function is a help for choosing this distance: it computes the productivity for a set of combinations of distances between the elements of the plant.

Usage

optimSombra(lat, G0dm, Ta = 25, modoSeg = "doble", modoRad = "prom", 
    previo, MAPA, BaseDatos, FormatoFecha = "%d/%m/%Y", Nm = 1, 
    BetaLim = 90, beta = abs(lat) - 10, alfa = 0, 
    iS = 2, alb = 0.2, 
    modulo = list(Vocn = 57.6, Iscn = 4.7, Vmn = 46.08, Imn = 4.35, 
        Ncs = 96, Ncp = 1, CoefVT = 0.0023, TONC = 47), 
    generador = list(Nms = 12, Nmp = 11), 
    inversor = list(Ki = c(0.01, 0.025, 0.05), Pinv = 25000, 
        Vmin = 420, Vmax = 750, Gumb = 20), 
    EffSys = list(ModQual = 3, ModDisp = 2, OhmDC = 1.5, OhmAC = 1.5, 
        MPP = 1, TrafoMT = 1, Disp = 0.5), 
    modoSombra = c("area", "prom"), 
    estruct = list(W = 23.11, L = 9.8, Nfilas = 2, Ncol = 8), 
    distancias = list(Leo = c(30, 50), Lns = c(20, 50), D = NULL), 
    res = 2, prog=TRUE)

Arguments

lat

see calcG0

G0dm

see calcG0

Ta

see calcG0

modoSeg

see fTheta

modoRad

see calcG0. If modoRad='prev' a previous result of this function prodSFCR is included in previo in order to obtain new results with the same irradiance on the horizont

previo

data.frame, needed when modoRad='prev'. It is the result of a previous use of this function

MAPA

see calcG0

BaseDatos

see calcG0

FormatoFecha

see calcG0

Nm

see calcG0

BetaLim

numeric, maximum value of the inclination angle (degrees) for a tracking surface. Its default value is 90 (no limitation))

beta

numeric, inclination angle of the surface (degrees). It is only needed when modoSeg='est'.

alfa

numeric, azimuth angle of the surface (degrees). It is positive to the West. It is only needed when modoSeg='est'. Its default value is alfa=0

iS

integer, degree of dirtiness. Its value must be included in the set (1,2,3,4). iS=1 corresponds to a clean surface while iS=4 is the selection for a dirty surface. Its default value is 2

alb

numeric, albedo reflection coefficient. Its default value is 0.2

modulo

see fProd

generador

see fProd

inversor

see fProd

EffSys

see fProd

modoSombra

character, defines the type of shadow calculation. In this version of the package the effect of the shadow is calculated as a proportional reduction of the circumsolar diffuse and direct irradiances. This type of approach is selected with modoSombra

estruct

list. When modoSeg='est' or modoSeg='horiz' only a component named L, which is the height (meters) of the tracker, is needed. For two-axis trackers (modoSeg='doble'), an additional component

distancias

list, whose three components are vector of length 2: [object Object],[object Object],[object Object]

res

numeric, difference (meters) between the different steps of the calculation

prog

logical, show a progress bar; default value is TRUE

Value

• list containing these elements:
• param
  list which contains the main parameters of the calculation.
• ref
  data.frame result of fProd without shadows effect. Therefore this is the performance of a system which is not affected by shadows, and will be used as the reference for the analysis
• S
  data.frame including the combinations of distances (defined by Leo, Lns, D and res, and obtained with expand.grid), the ROT value for each combination (where ROT, "Ratio de Ocupacion del Terreno", is the inverse value of the ground cover ratio), the shadows factor value (FS) and the yearly productivity (Yf)
• FS.loess
  local fitting with loess of the FS value where the predictors are Leo, Lns or D
• Yf.loess
  local fitting with loess of the Yf value where the predictors are Leo, Lns or D

Details

The result of this function is of class 'sombra'. A new method of plot for this class is defined (plot.sombra). Therefore plot(result) will show the graphical relation between the productivity and the distance between trackers or static surfaces.

References

• Perpiñán, O.: Grandes Centrales Fotovoltaicas: producción, seguimiento y ciclo de vida. PhD Thesis, UNED, 2008.http://e-spacio.uned.es/fez/view.php?pid=bibliuned:20080.

Perpiñán, O, Energía Solar Fotovoltaica, 2010. (http://procomun.wordpress.com/documentos/libroesf/)

See Also

prodSFCR, fSombra, fSombra6, fSombra2X, fSombraEst, fSombraHoriz

Examples

lat=37.2;#Sevilla
    G0dm=c(2766, 3491, 4494, 5912, 6989, 7742, 7919, 7027, 5369, 3562, 2814, 2179)
    
    ###Two-axis trackers
    distancias=list(Leo=c(30,50),Lns=c(20,50))

    #Monthly averages
    SombraM2x<-optimSombra(lat=lat,G0dm=G0dm, modoSeg='doble', 
        modoSombra=c('area','prom'), distancias=distancias, res=5)

    plot(SombraM2x)

    pLeo=xyplot(Yf~ROT,data=SombraM2x$S,groups=factor(Leo),type=c('l','g'))
    direct.label(pLeo,method=last.points)

    pLns=xyplot(Yf~ROT,data=SombraM2x$S,groups=factor(Lns),type=c('l','g'))
    direct.label(pLns,method=last.points)


    ###Horizontal axis tracker
    estruct=list(L=4.83);
    distancias=list(Leo=estruct$L*c(2,5));

    #Without backtracking
    Sombra12Horiz<-optimSombra(lat=lat,G0dm=G0dm, modoSeg='horiz',
        BetaLim=60,
        distancias=distancias, res=2,
        estruct=estruct,
        modoSombra='area')

    plot(Sombra12Horiz)

    xyplot(diff(Yf)~ROT[-1],data=Sombra12Horiz$S,type=c('l','g'))

    #with Backtracking
    Sombra12HorizBT<-optimSombra(lat=lat,G0dm=G0dm, modoSeg='horiz',
        BetaLim=60,
        distancias=distancias, res=1,
        estruct=estruct,
        modoSombra='bt')

    plot(Sombra12HorizBT)
    xyplot(diff(Yf)~ROT[-1],data=Sombra12HorizBT$S,type=c('l','g'))


    ###Fixed system
    estruct=list(L=5);
    distancias=list(D=estruct$L*c(1,3));
    Sombra12Est<-optimSombra(lat=lat,G0dm=G0dm, modoSeg='est',
        modoSombra='area', 
        distancias=distancias, res=1,
        estruct=estruct)

    plot(Sombra12Est)