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@inproceedings{Geske:2016:10.1109/IPEMC.2016.7512341,
author = {Geske, J and Green, R},
doi = {10.1109/IPEMC.2016.7512341},
pages = {524--529},
title = {Optimal storage investment and management under uncertainty},
url = {http://dx.doi.org/10.1109/IPEMC.2016.7512341},
year = {2016}
}

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TY  - CPAPER
AB  - © 2016 IEEE. 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.
AU  - Geske,J
AU  - Green,R
DO  - 10.1109/IPEMC.2016.7512341
EP  - 529
PY  - 2016///
SP  - 524
TI  - Optimal storage investment and management under uncertainty
UR  - http://dx.doi.org/10.1109/IPEMC.2016.7512341
ER  -

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