OptiWindNet Documentation¶
OptiWindNet: Wind Farm Electrical Network Optimizer
(distributed under the MIT License)
Python Package Index (PyPI) |
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Source code repository |
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Issue tracker |
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Jupyter notebooks used in this manual |
https://gitlab.windenergy.dtu.dk/TOPFARM/OptiWindNet/-/tree/main/docs/notebooks |
About OptiWindNet¶
OptiWindNet is an electrical network design tool for offshore wind farms developed at the Technical University of Denmark – DTU. Its built-in routers seek short feasible cable networks for a given turbine layout within the cable-laying boundaries. Cable length is used as a proxy for cost; when cable prices are supplied, the cost of the resulting network can also be reported. It provides high-level access to constructive-heuristic, meta-heuristic and exact optimization routers. See Objective and reported cost for the distinction between the length objective and reported cost.
The tool is distributed as the open-source Python package optiwindnet, which can be used either within an interactive Python session (e.g. Jupyter notebook) or as a library, by invoking OptiWindNet’s API directly from another application (e.g. TOPFARM, Ard).
What can OptiWindNet do?¶
Optimize the network of array cables (aka collection system, infield cables, internal grid, inter-array cables);
Route the cables to avoid exclusion zones and cable-to-cable crossings;
Assign cable types and calculate network costs;
Use different optimization approaches according to the preferred time/quality trade-off;
Employ user-provided models and objective functions within the mathematical optimization approach.
How this documentation is arranged¶
Start gets you running: Install, the Quick Start, and Which API?, which introduces the two APIs and helps you pick one.
Concepts explains what the tool computes (The cable routing problem) and how to choose an optimization approach (Optimization approaches). These pages are shared by both APIs and can be read before choosing one.
Network/Router API and Advanced API are the two sets of worked notebooks. Most notebooks have a counterpart in the other section that performs the same task.
Reference holds the lookup material, meant to be consulted rather than read through: the Task Index finds a page by what you are trying to do, plus the Glossary, Input Formats, Turbine Power and Cable Capacity, MILP Solvers, Warm-starting, MILP Formulation, Validation and the generated API Reference.
Papers holds the two scientific articles behind the tool: Framework Paper presents the framework and reproduces the computational experiments of the article below, while Dataset Paper presents the open database of routing solutions produced with it.
How to Cite¶
A peer-reviewed scientific article explaining the OptiWindNet framework and benchmarking it against state-of-the-art methods is available (open-access) at:
Mauricio Souza de Alencar, Tuhfe Göçmen, Nicolaos A. Cutululis, Flexible cable routing framework for wind farm collection system optimization, European Journal of Operational Research, 329(3):1037-1051, 2026, ISSN 0377-2217, https://doi.org/10.1016/j.ejor.2025.07.069.
The BibTeX entry is in Framework Paper, together with the notebooks that reproduce the article’s results.
A second article introduces OptiWindNet RouteSets, an open database of cable-routing solutions produced with OptiWindNet. It is under review; the preprint is open-access at:
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.
Cite it if you use the database, whose own DOI and BibTeX entry are in Dataset Paper.
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.