Offshore Oil and Gas Field Energy System Operational Optimisation (OOGESO)
Offshore Oil and Gas Energy System Operational Optimisation Model (oogeso)
Python module for modelling and analysing the energy system of offshore oil and gas fields, with renewable energy and storage integration.
Part of the Low Emission Centre (SP5).
Install latest Oogeso release from PyPi:
pip install oogeso
in order to use the plotting functionality you will need to install plotting libraries:
pip install matplotlib plotly seaborn
User guide and examples
The online user guide gives more information about how to specify input data and run a simulation case.
- CBC solver Clone or download the code and install it as a python package. I.e. navigate to the folder with the MANIFEST.in file and type:
git clone firstname.lastname@example.org:oogeso/oogeso.git
poetry install --no-root--no-root to not install the package itself, only the dependencies.
poetry run pytest tests
Local development in Docker
Alternatively you can run and develop the code using docker and the Dockerfile in the root folder.
GitHub Actions Pipelines
4 pipelines are defined.
- Build: Building and testing on multiple OS and python versions. Triggered on any push to GitHub.
- CBC-optimizer CI: Build and test oogeso with the CBC-solver and spesific cbc-tests.
- Release: Create release based on tags starting on v*.
- Publish: Publish the package to PyPi when a release is marked as published.
You are welcome to contribute to the improvement of the code.
- Use Issues to describe and track needed improvements and bug fixes
- Use branches for development and pull requests to merge into main
- Use Pre-commit hooks
Harald G Svendsen
SINTEF Energy Research
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.