Getting started

Open RAO (Remedial Action Optimizer) is an open-source toolbox that aims at providing a modular engine for remedial actions optimisation, part of the Linux Foundation Energy.

Useful links

Java

• GitHub

• 

A java tutorial is available here.

Python

Based on PyPowsybl, OpenRao can be used with Python.

• GitHub

• PyPowsybl documentation

A Jupyter notebook is defined here.

Start using OpenRao

• Mandatory input data are:

  • a network

  • a CRAC. CRAC objects are detailed here.

• You will also need to define a set of rao parameters.

• Outputs:

  • Step-by-step calculation is detailed in the logs. Learn more about how logs are configured here.

  • Rao results are defined in a json file, described here.

Understanding OpenRao

• The following pages describe how OpenRao works:

  • CASTOR, the RAO algorithm

  • Optimisation steps

  • Monitoring module

• For a fine understanding of the constraints defined in the Linear Problem, see this section.

Fine tuning your implementation of OpenRao

Check Combining performance and complexity to adapt your rao implementation.