pyCLARA

python Clustering of Lines And RAsters

Code developers

Kais Siala, Mohammad Youssed Mahfouz, Waleed Sattar Khan, Houssame Houmy

Documentation authors

Kais Siala, Waleed Sattar Khan, Houssame Houmy

Maintainers

Kais Siala <kais.siala@tum.de>

Organization

Chair of Renewable and Sustainable Energy Systems, Technical University of Munich

Version

1.0.0

Date

Jun 03, 2020

License

The model code is licensed under the GNU General Public License 3.0. This documentation is licensed under a Creative Commons Attribution 4.0 International license.

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 of the output regions

  • 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

Changes

version 1.0.0

This is the initial version.

Contents

Theory documentation

Continue here if you want to understand the concept of the model and learn more about clustering algorithms.

Dependencies

A list of the used libraries is available in the environment file:

name: geoclustering
channels:
  - defaults
  - conda-forge
dependencies:
  - pysal=1.14.4
  - pandas
  - geopandas=0.7.0
  - scikit-learn
  - libpysal
  - rasterio
  - networkx
prefix: D:\Miniconda3\envs\geoclustering

Bibliography

Indices and tables