R/NmgSFB.R

In solaR2: Radiation and Photovoltaic Systems

## NmgPVPS: no visible binding for global variable ‘Pnom’
## NmgPVPS: no visible binding for global variable ‘group.value’

if(getRversion() >= "2.15.1") globalVariables(c('Pnom', 'group.value'))

NmgPVPS <- function(pump, Pg, H, Gd, Ta = 30,
                    lambda = 0.0045, TONC = 47,
                    eta = 0.95, Gmax = 1200, t0 = 6, Nm = 6,
                    title = '', theme = custom.theme.2()){

    ##I build the type day by IEC procedure
    t <- seq(-t0, t0, l = 2*t0*Nm);
    d <- Gd/(Gmax*2*t0)
    s <- (d*pi/2-1)/(1-pi/4)
    G <- Gmax*cos(t/t0*pi/2)*(1+s*(1-cos(t/t0*pi/2)))
    G[G<0] <- 0
    G <- G/(sum(G,na.rm = 1)/Nm)*Gd
    Red <- expand.grid(G = G,Pnom = Pg,H = H,Ta = Ta)
    Red <- within(Red,{Tcm<-Ta+G*(TONC-20)/800
        Pdc = Pnom*G/1000*(1-lambda*(Tcm-25)) #Available DC power
        Pac = Pdc*eta})                       #Inverter yield

    res <- data.table(Red,Q = 0)

    for (i in seq_along(H)){
        fun <- fPump(pump, H[i])
        Cond <- res$H == H[i]
        x <- res$Pac[Cond]
        z <- res$Pdc[Cond]
        rango <- with(fun, (x >= lim[1] & x <= lim[2])) #I limit the power to the operating range of the pump.
        x[!rango] <- 0
        z[!rango] <- 0
        y <- res$Q[Cond]
        y[rango] <- fun$fQ(x[rango])
        res$Q[Cond] <- y
        res$Pac[Cond] <- x
        res$Pdc[Cond] <- z
    }

    resumen <- res[, lapply(.SD, function(x)sum(x, na.rm = 1)/Nm),
                   by = .(Pnom, H)]
    param <- list(pump = pump, Pg = Pg, H = H, Gd = Gd, Ta = Ta,
               lambda = lambda, TONC = TONC, eta = eta,
               Gmax = Gmax, t0 = t0, Nm = Nm)


###Abacus with common X-axes

    ##I check if I have the lattice package available, which should have been loaded in .First.lib
    lattice.disp <- ("lattice" %in% .packages())
    latticeExtra.disp <- ("latticeExtra" %in% .packages())
    if (lattice.disp && latticeExtra.disp){
        tema <- theme
        tema1 <- modifyList(tema, list(layout.width = list(panel = 1,
                                       ylab = 2, axis.left = 1.0,
                                       left.padding = 1, ylab.axis.padding = 1,
                                       axis.panel = 1)))
        tema2 <- modifyList(tema, list(layout.width = list(panel = 1,
                                       ylab = 2, axis.left = 1.0, left.padding = 1,
                                       ylab.axis.padding = 1, axis.panel = 1)))
        temaT <- modifyList(tema, list(layout.heights = list(panel = c(1, 1))))
        p1 <- xyplot(Q~Pdc, groups = H, data = resumen,
                     ylab = "Qd (m\u00b3/d)",type = c('l','g'),
                     par.settings = tema1)

        p1lab <- p1+glayer(panel.text(x[1], y[1], group.value, pos = 2, cex = 0.7))

        ##I paint the linear regression because Pnom~Pdc depends on the height.
        p2 <- xyplot(Pnom~Pdc, groups = H, data = resumen,
                     ylab = "Pg",type = c('l','g'), #type = c('smooth','g'),
                     par.settings = tema2)
        p2lab <- p2+glayer(panel.text(x[1], y[1], group.value, pos = 2, cex = 0.7))

        p <- update(c(p1lab, p2lab, x.same = TRUE),
                    main = paste(title, '\nSP', pump$Qn, 'A', pump$stages, ' ',
                               'Gd ', Gd/1000," kWh/m\u00b2",sep = ''),
                    layout = c(1, 2),
                    scales = list(x = list(draw = FALSE)),
                    xlab = '',              
                    ylab = list(c("Qd (m\u00b3/d)","Pg (Wp)"), y = c(1/4, 3/4)),
                    par.settings = temaT
                    )
        print(p)
        result <- list(I = res,D = resumen, plot = p, param = param)
    } else {
        warning('lattice, latticeExtra packages are not all available. Thus, the plot could not be created')
        result <- list(I = res, D = resumen, param = param)
    }
}