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**Harvard**

Georgiadis, G. och Papatriantafilou, M. (2014) *Dealing with storage without forecasts in Smart Grids: problem transformation and online scheduling algorithm*.

** BibTeX **

@conference{

Georgiadis2014,

author={Georgiadis, Giorgos and Papatriantafilou, Marina},

title={Dealing with storage without forecasts in Smart Grids: problem transformation and online scheduling algorithm},

booktitle={29th Annual ACM Symposium on Applied Computing, SAC 2014; Gyeongju; South Korea; 24 March 2014 through 28 March 2014},

isbn={978-1-4503-2469-4},

pages={518-524},

abstract={Renewable and distributed energy sources are today possible
but these technologies bring benefits as well as challenges, such as their intermittent nature, that leads to utilization problems for the power grid. On the other hand, upcoming storage technologies, such as electric vehicles, hold the potential to store and utilize this intermittent supply at a later time but bring challenges of their own, for example efficient storage utilization and intermittent energy demand.
In this paper we propose a novel modeling of the problem of
unforecasted energy dispatch with storage as an online
scheduling problem of tasks on machines, by transforming
time constraints of energy requests into equivalent machine
constraints as well as by modeling energy storage through the extension of existing online scheduling techniques with the concept of \emph{load credit}. Based on this transformation, we also present an algorithm that dispatches load and utilizes efficiently any storage capabilities in order to mitigate the effect of unreliable or non-existent demand forecasts, and we prove that the resulting solution's competitive ratio is within a logarithmic factor of the optimal offline solution. Finally, we provide an extensive simulation study for a variety of scenarios based on data from a large network of consumers, showing that the presented algorithm is highly competitive even to methods that assume exact knowledge about the demand requests.
},

year={2014},

}

** RefWorks **

RT Conference Proceedings

SR Electronic

ID 193991

A1 Georgiadis, Giorgos

A1 Papatriantafilou, Marina

T1 Dealing with storage without forecasts in Smart Grids: problem transformation and online scheduling algorithm

YR 2014

T2 29th Annual ACM Symposium on Applied Computing, SAC 2014; Gyeongju; South Korea; 24 March 2014 through 28 March 2014

SN 978-1-4503-2469-4

SP 518

OP 524

AB Renewable and distributed energy sources are today possible
but these technologies bring benefits as well as challenges, such as their intermittent nature, that leads to utilization problems for the power grid. On the other hand, upcoming storage technologies, such as electric vehicles, hold the potential to store and utilize this intermittent supply at a later time but bring challenges of their own, for example efficient storage utilization and intermittent energy demand.
In this paper we propose a novel modeling of the problem of
unforecasted energy dispatch with storage as an online
scheduling problem of tasks on machines, by transforming
time constraints of energy requests into equivalent machine
constraints as well as by modeling energy storage through the extension of existing online scheduling techniques with the concept of \emph{load credit}. Based on this transformation, we also present an algorithm that dispatches load and utilizes efficiently any storage capabilities in order to mitigate the effect of unreliable or non-existent demand forecasts, and we prove that the resulting solution's competitive ratio is within a logarithmic factor of the optimal offline solution. Finally, we provide an extensive simulation study for a variety of scenarios based on data from a large network of consumers, showing that the presented algorithm is highly competitive even to methods that assume exact knowledge about the demand requests.

LA eng

DO 10.1145/2554850.2554943

LK http://dx.doi.org/10.1145/2554850.2554943

OL 30