Version 2.0.0

In tsam’s latest release (2.0.0) the following functionalities were included:

• A new comprehensive structure that allows for free cross-combination of clustering algorithms and cluster representations, e.g. centroids or medoids.
• A novel cluster representation method that precisely replicates the original time series value distribution in the aggregated time series based on “Hoffmann, Kotzur and Stolten (2021): The Pareto-Optimal Temporal Aggregation of Energy System Models (https://arxiv.org/abs/2111.12072)”
• Maxoids as representation algorithm which represents time series by outliers only based on “Sifa and Bauckhage (2017): Online k-Maxoids clustering”
• K-medoids contiguity: An algorithm based on “Oehrlein and Hauner (2017): A cutting-plane method for adjacency-constrained spatial aggregation” that accounts for contiguity constraints to e.g. cluster only time series in neighboring regions

Version 1.1.2

This tsam release (1.1.2) includes the following new functionalities

• Added first version of the k-medoid contiguity algorithm

Version 1.1.1

This tsam release (1.1.1) includes

• Significantly increased test coverage
• Separation between clustering and representation, i.e. for clustering algorithms like Ward’s hierarchical clustering algorithm the representation by medoids or centroids can now freely be chosen.

Include build testing

v1.01

prepare new release including testing

First pypi release

v0.9.9

finalize pypi release

Clarify aggregation output structure

• add second example which illustrates the output of the aggregation
• add the second publication about storage modeling in readme
• modify usable attributes to properties

v0.9.4

• Improvement of extreme periods
• Move to MIT license

v0.9.3

Patch to first public version with minor bug fixes

v0.9.2

First public release

Features:

• different aggregation methods implemented (averaging, k-mean, exact k-medoid, hierarchical), which are based on scikit-learn or pyomo
• flexible integration of extreme periods as own cluster centers
• weighting for the case of multidimensional time-series to represent their relevance

v0.9.1

First public release of tsam