add_holidays_mid_term

This function adds a dummy variable for holidays to the mid-term data series. Information on the holidays is retrieved from "https://date.nager.at/api/v3/publicholidays/".

Advanced forecasting algorithms for long-term energy demand at the
national or regional level. The methodology is based on Grandón et al. (2024)
<doi:10.1016/j.apenergy.2023.122249>; Zimmermann & Ziel (2024)
<doi:10.1016/j.apenergy.2025.125444>. Real-time data, including power demand, weather conditions, and macroeconomic indicators, are provided through automated API integration with various institutions. The modular approach maintains transparency on the various model selection processes and encompasses the ability to be adapted to individual needs. 'oRaklE' tries to help facilitating robust decision-making in energy management and planning.

Johannes Schwenzer

oRaklE

Multi-Horizon Electricity Demand Forecasting in High Resolution

Simone Maxand

Tatiana Gonzalez Grandón

add_holidays_mid_term function

<dl><dt>midterm_data</dt>
<dd>The mid-term data series resulting from the function <code>decompose_load_data</code>.</dd></dl>

Arguments

Add holidays to the mid-term series — add_holidays_mid_term

<dl>

<dt>midterm_data</dt>
<dd>The mid-term data series resulting from the function <code>decompose_load_data</code>.</dd>

</dl>

add_holidays_mid_term: Add holidays to the mid-term series

Description

Usage

Value

Arguments

See Also

Examples