Redispatch Volumes Forecasting

This repository includes the code for the paper "Analyzing and Forecasting Redispatch Volumes in Germany: Insights into Market-Based Redispatch Mechanisms".

Key Features

• Analysis of redispatch volumes, generation, load and day-ahead prices in 2021 - 2024
• Redispatch volumes forecasting for each German TSO control area using ARIMAX and LSTM models

Data Sources

The data used in this project was obtained from the following open sources:

• Netztransparenz.DE:
  • Redispatch volumes in Germany
• ENTSO-E Transparency Platform:
  • Generation and load data for the DE-LU bidding zone
• New ENTSO-E Transparency Platform:
  • Day-ahead prices for the DE-LU bidding zone

Usage

Install requirements:

pip install -r requirements.txt

There are two main Jupyter notebooks:

• data_parsing.ipynb: creates redispatch, generation, load and prices datasets that are used in the forecasting framework

• forecast.ipynb: includes the main methods used for data analysis and forecasting