example_midterm_future_predictions: Example Midterm Future Predictions Data

Description

This dataset extends the mid-term electricity demand predictions from example_midterm_predictions until the year 2028.

Usage

example_midterm_future_predictions

Arguments

Format

A data frame with 4,380 rows and 46 columns:

country: The country, represented by the ISO2C country code (e.g., FR for France).
date: The date (in YYYY-MM-DD format).
year: The respective year.
month: The respective month.
day: The respective day.
wday: The type of weekday (e.g., Sun, Mon)
avg_hourly_demand: The average hourly electricity demand (in megawatts) for the day.
seasonal_avg_hourly_demand: The seasonal average hourly demand (in megawatts) for the day.
holiday: Indicates whether the day is a public holiday (1 for holiday, 0 for non-holiday).
weighted_temperature: The weighted average temperature for France on that day (in degrees Celsius).
Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Nov, Dec: Monthly dummy variables for January through December, indicating the respective month (1 if the date belongs to the month, 0 otherwise).
Sun, Mon, Tue, Wed, Thu, Fri, Sat: Weekly dummy variables for Sunday through Saturday, indicating the respective weekday (1 if the date is the specific weekday, 0 otherwise).
HD: The weighted temperature converted to heating degree days.
CD: The weighted temperature converted to cooling degree days.
HD2: The squared heating degree days (HD).
HD3: The cubed heating degree days (HD).
CD2: The squared cooling degree days (CD).
CD3: The cubed cooling degree days (CD).
weighted_temperature2: The squared weighted temperature.
weighted_temperature3: The cubed weighted temperature.
HDlag1: Lagged value of heating degree days (1 day).
HDlag2: Lagged value of heating degree days (2 days).
CDlag1: Lagged value of cooling degree days (1 day).
CDlag2: Lagged value of cooling degree days (2 days).
weighted_temperaturelag1: Lagged weighted temperature (1 day).
weighted_temperaturelag2: Lagged weighted temperature (2 days).
midterm_model_fit: model predictions for the seasonal mid-term component.
end_of_year: Binary dummy variable to account for lower demand between Christmas and New Year's Evening. Starts at 22nd December.
test_set_steps: Number of days used in the test set for model evaluation.
example: A boolean indicator to mark this dataset as an example dataset.