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).

Getting started

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.

• User guide

Local installation

Prerequisite:

• Poetry
• Pre-commit
• 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:

Install dependencies

1. git clone git@github.com:oogeso/oogeso.git
2. cd oogeso
3. poetry install --no-root --no-root to not install the package itself, only the dependencies.
4. poetry shell
5. 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.

1. Build: Building and testing on multiple OS and python versions. Triggered on any push to GitHub.
2. CBC-optimizer CI: Build and test oogeso with the CBC-solver and spesific cbc-tests.
3. Release: Create release based on tags starting on v*.
4. Publish: Publish the package to PyPi when a release is marked as published.

Contribute

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

Contact

Harald G Svendsen
SINTEF Energy Research