short_term_lm: Short-term forecast

In oRaklE: Multi-Horizon Electricity Demand Forecasting in High Resolution

Short-term forecast

Description

The short-term load series is forecasted based on the provided hourly load data.

Usage

short_term_lm(
  shortterm_demand_data,
  test_set_steps = 17520,
  data_directory = tempdir(),
  verbose = FALSE
)

Arguments

shortterm_demand_data	Dataframe. Containing the short-term load data from decompose_load_data and the added holiday dummy resulting from add_holidays_short_term.
test_set_steps	Integer. Number of hours used for the test set. The default value of 17520 equals two years (2 * 8760 hours).
data_directory	The path to the directory where the data, plots, and models will be saved. The default is set to a temporary directory.
verbose	A boolean value indicating if you want the generated plots to be shown (set to TRUE if yes).

Value

A list with the dataframe with the input data and results. A list with the plotted result for the complete timeseries and two sample weeks. And a list with the the best model for each type of month and type of day (84 in total with 12 different months times 7 types of weekdays). The dataset, plots, and the models are saved in the respective folder for the country.

shortterm_predictions

A dataframe with the input data and additional columns for the respective hour, test_set_steps, and for the model predictions.

shortterm_plots

A list with the full plot and a plot for two sample weeks.

shortterm_models

A list with the respective models for each month and type of day.

Examples

example_shortterm_predictions <- short_term_lm(example_shortterm_demand_data)

oRaklE documentation built on June 8, 2025, 12:41 p.m.