AUDem {qgam}

Australian electricity demand data

Description

Data set on electricity demand from Sidney, Australia. The data has been downloaded from https://www.ausgrid.com.au, and it originally contained electricity demand from 300 customers, at 30min resolution. We discarded 53 customers because their demand was too irregular, and we integrated the demand data with temperature data from the National Climatic Data Center, covering the same period.

Usage

data(AUDem)

Format

AUDem is a list, where AUDem$meanDem is a data.frame containing the following variables:

doy

the day of the year, from 1 to 365;

tod

the time of day, ranging from 18 to 22, where 18 indicates the period from 17:00 to 17:30, 18.5 the period from 17:30 to 18:00 and so on;

dem

the demand (in KW) during a 30min period, averaged over the 247 households;

dow

factor variable indicating the day of the week;

temp

the external temperature at Sidney airport, in degrees Celsius;

date

local date and time;

dem48

the lagged mean demand, that is the average demand (dem) during the same 30min period of the previous day;

The second element is AUDem$qDem48 which is a matrix with as many rows as AUDem$meanDem. Each rows contains 20 equally spaced empirical quantiles of the lagged individual electricity demand of the 247 customers.

Value

A list where AUDem$meanDem is a data.frame and AUDem$qDem48 a matrix.

Examples

library(qgam)
data(AUDem)
  
# Mean demand over the period
plot(AUDem$meanDem$dem, type = 'l')
  
# 20 quantiles of individual demand over 5 days
matplot(seq(0.01, 0.99, length.out = 20), 
        t(AUDem$qDem48[c(1, 50, 75, 100, 250), ]), 
        type = 'l', 
        ylab = "Electricity demand (KW)",
        xlab = expression("Probability level " * "(p)"), 
        lty = 1)