Load curve of an habitation
The data frame provides electric consumption of an habitation in France over one month.
data("LoadCurve")The data is the electric consumption of an habitation in Kilovolt-amps (kVA) every 10 minutes during one month. The habitation has a contract that allows a maximum power of 6 kVA.A list of 2 elements.
$data : a data frame with 24126 observations for 2 variablesTimethe number of day since the 1st of January, 1970.
Valuethe value of the electric consumtion in kVA.
$Tgrid : A grid of time to perform the procedure.Electricite Reseau Distribution France
data("LoadCurve")
X<-LoadCurve$data$Value
days<-LoadCurve$data$Time
Tgrid <- seq(min(days), max(days), length = 400)
new.Tgrid <- LoadCurve$Tgrid
## Not run: #For computing time purpose
# Choice of the bandwidth by cross validation.
# We choose the truncated Gaussian kernel and the critical value
# of the goodness-of-fit test 3.4.
# As the computing time is high, we give the value of the bandwidth.
#hgrid <- bandwidth.grid(0.8, 5, 60)
#hcv<-bandwidth.CV(X=X, t=days, new.Tgrid, hgrid, pcv = 0.99,
# kernel = TruncGauss.kernel, CritVal = 3.4, plot = FALSE)
#h.cv <- hcv$h.cv
h.cv <- 3.444261
HH<-hill.ts(X, days, new.Tgrid, h=h.cv, kernel = TruncGauss.kernel, CritVal = 3.4)
Quant<-rep(NA,length(Tgrid))
Quant[match(new.Tgrid, Tgrid)]<-as.numeric(predict(HH,
newdata = 0.99, type = "quantile")$y)
Date<-as.POSIXct(days*86400, origin = "1970-01-01",
tz = "Europe/Paris")
plot(Date, X/1000, ylim = c(0, 8),
type = "l", ylab = "Electric consumption (kVA)", xlab = "Time")
lines(as.POSIXlt((Tgrid)*86400, origin = "1970-01-01",
tz = "Europe/Paris"), Quant/1000, col = "red")
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.