Optimal storage investment and management under uncertainty

Subject of this analysis is to show how storage is operated optimally under renewable and load uncertainty in the electricity system context. We estimate a homogeneous Markov Chain representation of the residual load in Germany in 2014 on an hourly basis and design a very simple dynamic stochastic electricity system model with non-intermittent generation technologies and storage. We compare these results to perfect foresight findings and identify a significant over estimation of the storage potential under perfect foresight.

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