Website | Docs | Install Guide | Tutorial
ProLoaF is a probabilistic load forecasting project.
Installation
First, clone this Repository and initialize the submodules:
git clone --recurse-submodule https://git.rwth-aachen.de/acs/public/automation/plf/proloaf.git
or if you have already cloned the project and you are missing e.g. the open data directory for execution run:
git submodule update --init --recursive
To install all required packages first run:
pip install -r requirements.txt
On low RAM machines the option
pip install -r requirements.txt --no-cache-dir
might be necessary.
ProLoaF supports Python 3.6 and higher. For further information see Getting Started
Gettings started, Key Capabilities, Example Workflows & References
To keep all infos on what you can do with ProLoaF and how to get there, our documentation overview, is the place where you'll find all answers.
Related Publications
G. Gürses-Tran, H. Flamme, and A. Monti, "Probabilistic Load Forecasting for Day-Ahead Congestion Mitigation," The 16th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2020, 2020-08-18 - 2020-08-21, Liège, Belgium, ISBN 978-1-7281-2822-1, Access Online
License
This project is licensed to the Apache Software Foundation (ASF).