python Clustering of Lines And RAsters: a tool to cluster high-resolution spatial data (rasters or polylines connecting Voronoi polygons) into contiguous, homogeneous regions.

Features

• Clustering of one or multiple high-resolution rasters, such as wind resource maps or load density maps
• Supported aggregation functions: average, sum, or density
• Combination of k-means and max-p algorithms, to ensure contiguity
• Clustering of grid data using a hierarchical algorithm
• Flexibility in the number of polygons obtained

Applications

This code is useful if:

• You want to obtain regions for energy system models with homogeneous characteristics (e.g. similar wind potential)
• You want to cluster regions based on several characteristics simultaneously
• You want to take into account grid restrictions when defining regions for power system modeling

Related publications

• Siala, Kais; Mahfouz, Mohammad Youssef: Impact of the choice of regions on energy system models. Energy Strategy Reviews 25, 2019, 75-85.

Contributors ✨

Thanks goes to these wonderful people (emoji key):

kais-siala 💻 📖 💡 🤔 🚧 👀 📢

HoussameH 💻 📖

Waleed Sattar Khan 💻 📖

MYMahfouz 💻 🤔

molarana 🎨

lodersky 💻 👀

This project follows the all-contributors specification. Contributions of any kind welcome!

Please cite as

We prefer that you cite the original publication, where the tool was introduced:

• Siala, Kais; Mahfouz, Mohammad Youssef: Impact of the choice of regions on energy system models. Energy Strategy Reviews 25, 2019, 75-85.

If you are using a new feature that was not part of the publication, and would like to cite it:

• Kais Siala, Houssame Houmy, Waleed Sattar Khan, & Mohammad Youssef Mahfouz. (2020, June 1). tum-ens/pyCLARA: python Clustering of Lines And RAsters (Version v1.0.0). Zenodo. http://doi.org/10.5281/zenodo.3872273