tsam was originally designed for reducing the computational load for large-scale energy system optimization models. If you are interested in that purpose of time series aggregation, you can find a detailed review about that topic here. If you are further interested in the impact of time series aggregation on the cost-optimal results on different energy system use cases, you can find a publication which validates the methods and describes their cababilites via the following link. A second publication introduces a method how to model model state variables (e.g. the state of charge of energy storage components) between the aggregated typical periods which can be found here. Finally yet importantly the potential of time series aggregation to simplify mixed integer linear problems is investigated here.
The publications about time series aggregation for energy system optimization models published alongside the development of tsam are listed below:
- Kotzur et al. (2018):
Impact of different time series aggregation methods on optimal energy system design - Kotzur et al. (2018):
Time series aggregation for energy system design: Modeling seasonal storage - Hoffmann et al. (2020):
A Review on Time Series Aggregation Methods for Energy System Models - Hoffmann et al. (2022):
The Pareto-Optimal Temporal Aggregation of Energy System Models <https://www.sciencedirect.com/science/article/abs/pii/S0306261922004342>