OptiWindNet

Tool for designing offshore wind farm electrical cable networks. Its built-in routers use cable length as a proxy for cost; when cable prices are supplied, OptiWindNet reports the cost of the resulting network, which need not be the minimum-cost network.

Documentation: optiwindnet.readthedocs.io
Quickstart Download the Jupyter notebooks used in the documentation. Report an issue (at GitHub mirror) API Reference How to Cite

Installation

pip install optiwindnet

or

conda install --channel conda-forge optiwindnet

Detailed instructions in Installation.

Requirements

OptiWindNet requires Python version 3.11+ (tested with 3.11-14). The last version to support Python 3.10 was v0.0.6.

The use of a Python virtual environment is recommended. OptiWindNet's dependencies (except for MILP solvers, see docs) will be installed automatically when using pip install optiwindnet or conda install optiwindnet.

One may optionally pre-install the dependencies in a python environment by using either:

• requirements.txt: pip install -r requirements.txt
• environment.yml: conda env create -f environment.yml (name: optiwindnet_env)

Papers

The methodology implemented in OptiWindNet is described in the peer-reviewed scientific article:

• Mauricio Souza de Alencar, Tuhfe Göçmen, Nicolaos A. Cutululis, Flexible cable routing framework for wind farm collection system optimization, European Journal of Operational Research, 2025, ISSN 0377-2217, https://doi.org/10.1016/j.ejor.2025.07.069.

@article{SOUZADEALENCAR20261037,
  title = {Flexible cable routing framework for wind farm collection system optimization},
  journal = {European Journal of Operational Research},
  volume = {329},
  number = {3},
  pages = {1037-1051},
  year = {2026},
  issn = {0377-2217},
  doi = {https://doi.org/10.1016/j.ejor.2025.07.069},
  url = {https://www.sciencedirect.com/science/article/pii/S0377221725005946},
  author = {Mauricio {Souza de Alencar} and Tuhfe Göçmen and Nicolaos A. Cutululis},
  keywords = {Combinatorial optimization, Network design, Collection system, Wind farm},
}

A second article introduces OptiWindNet RouteSets, an open database of cable-routing solutions produced with OptiWindNet (Zenodo). It is under review; the preprint is open-access:

• Mauricio Souza de Alencar, Tuhfe Göçmen, Nicolaos A. Cutululis, OptiWindNet RouteSets: a solver-diverse benchmark dataset for the offshore wind-farm cable routing problem, Wind Energy Science Discussions [preprint], 2026, https://doi.org/10.5194/wes-2026-124, in review.

@Article{wes-2026-124,
  author = {Souza de Alencar, M. and G\"o\c{c}men, T. and Cutululis, N. A.},
  title = {OptiWindNet RouteSets: a solver-diverse benchmark dataset for the offshore wind-farm cable routing problem},
  journal = {Wind Energy Science Discussions},
  volume = {2026},
  year = {2026},
  pages = {1--13},
  url = {https://wes.copernicus.org/preprints/wes-2026-124/},
  doi = {10.5194/wes-2026-124},
}

Details on the database and its analyses are in Dataset Paper.

Citing OptiWindNet

The OptiWindNet software package can be cited (unversioned) as:

Souza de Alencar, M., Arasteh, A., & Friis-Møller, M. (2026). OptiWindNet by DTU Wind Energy. Zenodo. https://doi.org/10.5281/zenodo.18388438

To cite a specific version, get the version-specific DOI at OptiWindNet's entry at Zenodo. Select the desired version on the right column and use one of the ready-to-use citation formats available at the bottom right of that page.

Acknowledgements

The development of OptiWindNet was carried out as part of a Ph.D. project at the Technical University of Denmark (DTU Wind), financially supported by the Independent Research Fund Denmark / Danmarks Frie Forskningsfond (DFF) under grant no. 1127-00188B, project Integrated Design of Offshore Wind Power Plants.

The heuristics implemented in this repository (release 0.0.1) are presented and analyzed in the MSc thesis Optimization heuristics for offshore wind power plant collection systems design (DTU Wind - Technical University of Denmark, July 4, 2022).

The meta-heuristic used is vidalt/HGS-CVRP — a modern implementation of the hybrid genetic search (HGS) algorithm specialized to the capacitated vehicle routing problem (CVRP), including an additional neighborhood called SWAP* — via its Python bindings mdealencar/HybGenSea.

The cable routing relies on a navigation mesh generated by the library artem-ogre/CDT (Constrained Delaunay Triangulation, C++) via its Python bindings artem-ogre/PythonCDT.