The aggregation of time series is a common approach to reduce the temporal complexity of energy system models. Yet, the modeling results are not always reliable and so far, we have little knowledge about the causes. This gap is addressed in the thesis and relevant time series parameters are identified and transferred to aggregated time series by analyzing the interaction between time series and model. The improved representation of these reduces systematic deviations and makes the results more robust.
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The aggregation of time series is a common approach to reduce the temporal complexity of energy system models. Yet, the modeling results are not always reliable and so far, we have little knowledge about the causes. This gap is addressed in the thesis and relevant time series parameters are identified and transferred to aggregated time series by analyzing the interaction between time series and model. The improved representation of these reduces systematic deviations and makes the results more r...
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