Improving accuracy of energy system models for an efficient energy transition: basis-oriented aggregation and machine learning

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In this talk, we present the results of applying a recently developed method, called Basis-Oriented time series aggregation, to improve the tractability of energy system models. We use machine learning techniques on previous runs to identify independent partitions of the time index that allow for a parallelized run of the model; greatly improving the running times of large scale optimization models.