.. _further_reading: ############### Further Reading ############### 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 capabilities 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 `_ * | Kannengießer et al. (2019): | `Reducing Computational Load for Mixed Integer Linear Programming: An Example for a District and an Island Energy System `_ * | 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 `