example_full_model_predictions: Example Full Model Predictions Data

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

Example Full Model Predictions Data

Description

This dataset combines the results from long_term_lm, mid_term_lm, and short_term_lm into the final predictions of hourly electricity demand for France from 2017 until 2021.

Usage

example_full_model_predictions

Format

A data frame with 43800 rows and 12 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)

hour

The respective hour of the day.

hourly_demand

The actual hourly electricity demand (in megawatts).

long_term_model

The predicted long-term trend (yearly average of hourly demand) from the best long-term forecasting model.

mid_term_model

The predicted mid-term seasonality (daily minus yearly average of hourly demand) from the best mid-term forecasting model.

short_term_model

The predicted short-term seasonality (actual hourly demand minus the long-term trend minus the mid-term seasonality) from the best short-term forecasting model.

complete_model

Final predicted electricity demand for each hour. Derived by adding the results from the long-, mid-, and short-term components.

Source

demand data: Transparency Platform of the European Network of Transmission System Operators for Electricity (ENTSO-E, https://transparency.entsoe.eu/); holidays: https://date.nager.at/api/v3/publicholidays/

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