Self-Organising Algorithms for Residential Demand Response
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2014Access:
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Adam Taylor, Edgar Galv?n-L?pez, Ivana Dusparic, Colin Harris, Andrei Marinescu, Siobh?n Clarke and Vinny Cahill, Self-Organising Algorithms for Residential Demand Response, Proceedings IEEE Conference on Technologies for Sustainability ? Engineering and the Environment (SusTech 2014), IEEE Conference on Technologies for Sustainability - Engineering and the Environment (SusTech 2014), 24-26 July, IEEE, 2014, 55-60Download Item:
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Abstract:
Residential Demand Response has shown promising
results in smart grid applications. It can be achieved manually
or autonomously. The variety of algorithms applied to achieve
autonomous Demand Response have lacked a common baseline.
The selection of testing environment is typically skewed by the
desire to find one in which a particular algorithm performs well.
This work evaluates several algorithms in a common evaluation
environment. Which has been designed to encompass the range of
conditions in a typical Residential Demand Response application.
The environments described exhibit the following characteristics:
non-stationary, dynamic, multi-actor, multi-objective. These char-
acteristics will then be used to provide heuristics for algorithm
selection.
The algorithms used were selected to cover the spectrum of
possible approaches to Demand Response. Some are centralised,
others distributed. There are collaborative approaches and non-
collaborative ones. Some are learning based, others require
no training. This work provides criteria for which particular
algorithms should be applied to a given application.
Author's Homepage:
http://people.tcd.ie/sclarkehttp://people.tcd.ie/vjcahill
http://people.tcd.ie/duspari
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Proceedings IEEE Conference on Technologies for Sustainability ? Engineering and the Environment (SusTech 2014)IEEE Conference on Technologies for Sustainability - Engineering and the Environment (SusTech 2014)
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Computer ScienceSubject (TCD):
Smart & Sustainable PlanetDOI:
http://dx.doi.org/10.1109/sustech.2014.7046218Licences: