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Energy Systems
Published in: Energy Systems 3/2014

01-09-2014 | Original Paper

A stochastic dynamic programming model for co-optimization of distributed energy storage

Authors: Xiaomin Xi, Ramteen Sioshansi, Vincenzo Marano

Published in: Energy Systems | Issue 3/2014

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Abstract

We develop a stochastic dynamic programming model that co-optimizes the use of energy storage for multiple applications, such as energy, capacity, and backup services, while accounting for market and system uncertainty. Using the example of a battery that has been installed in a home as a distributed storage device, we demonstrate the ability of the model to co-optimize services that ‘compete’ for the capacity of the battery. We also show that these multiple uses of a battery can provide substantive value.
previous article Mathematical optimization for challenging network planning problems in unbundled liberalized gas markets
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Appendix
Available only for authorised users
Footnotes
1
Pumped hydroelectric storage (PHS) accounts for most currently installed storage capacity [21] and interest in compressed-air energy storage (CAES) is increasing [22]. Due to their physical attributes and geological requirements, PHS and CAES are both utility-scale storage technologies.
 
2
A kW-h, which is a unit for one kW of AS capacity provided for 1 h, should be distinguished from a kWh, which is a unit of energy.
 
3
This is also why we define \(\delta _t^u\) and \(\delta _t^d\) as the hour-\((t-1)\) ratios, due to our time definition convention.
 
4
The scenario tree only has 20 sample paths because the resulting two-stage model is computationally intractable with a larger tree.
 
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Metadata
Title
A stochastic dynamic programming model for co-optimization of distributed energy storage
Authors
Xiaomin Xi
Ramteen Sioshansi
Vincenzo Marano
Publication date
01-09-2014
Publisher
Springer Berlin Heidelberg
Published in
Energy Systems / Issue 3/2014
Print ISSN: 1868-3967
Electronic ISSN: 1868-3975
DOI
https://doi.org/10.1007/s12667-013-0100-6

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