index.rst

Welcome to tsam's documentation!

tsam - time series aggregation module

tsam is a python package which uses different machine learning algorithms for the aggregation of typical periods. It is applicable for all type of time series, either weather data, load data or both simultaneously. The module is able to significantly reduce input time series for energy system models, and therefore the model's complexity and computational time.

To use tsam, jump to the Section Getting Started<getting_started>.

The concept of tsam is that scientists, programmers and anyone who is interested all around the world can use tsam to aggregate their time series whatever they might be used for. Therefore, tsam is open-source available on GitHub and open for collaboration. The authors of both, the program and the publications, kindly request you to cite their work listed in the Further Reading Section <further_reading> if tsam is used in a scientific context.

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