Electricity prices in the new deregulated electricity market across Europe are now formulated by market forces while the scarcity of infrastructure resources that are necessary in order to serve the steadily increasing demand is becoming more profound. An instrument to efficiently cope with this situation is demand side management, especially when applied to small electricity consumers. The efficient support of this task necessitates the utilization of efficient computation tools in order to manage the huge and heterogeneous amount of data involved in this process. A model based on the Semantic Web notions is proposed in this paper for the efficient modeling of customer characteristics, aiming to assist an electricity provider in the development of his customer's portfolio in order to participate in a demand side bidding process.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
International Energy Agency: Demand Side Bidding for Smaller Customers. Technical report, IEA demand side management programme, www.iea.org (2005)
Directive 2003/54/EC of the European Parliament and of the Council of concerning common rules for the internal market in electricity, http://europa.eu.int (2003)
European Transmission System Operators: Current state of balance management in South East Europe, www.etso-net.org June (2006)
Bendel, C., Nestle, D.: Decentralized electrical power generators in the low voltage grid-development of a technical and economical integration study. International Journal of Distributed Energy Resources. Vol 1, No.1, (2005)
Towards Smart power networks-Lessons learned from European research FP5 projects, http://ec.europa.eu/research/energy
Kofod, C.: DR by Danish Domestic Customers using Direct Electric Heating. Technical Report, EU Efflocom project, http://www.energinet.dk (2007)
OWL Web Ontology Language Reference W3C Recommendation, http://www.w3.org/TR/2004/REC-owl-ref-20040210/
Radcliffe, Nicholas J.: The Algebra of Genetic Algorithms, Annals of Maths and Artificial Intelligence. Vol 10, 339–384 (1994)
Horrocks, Ian., Lei. Li.: A Software Framework for Matchmaking Based on Semantic Web Technology. International Journal of Electronic Commerce. Vol. 8, Iss. 4, 39–60 (2004)
Shum, S., Motta, E., Domingue, J.: ScholOnto: An Ontology-Based Digital Library Server for Research Documents and Discourse. International Journal on Digital Libraries. Vol. 3, Iss. 3, 237–248 (2000)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer Science+Business Media, LLC
About this paper
Cite this paper
Tilipakis, N., Douligeris, C., Neris, A. (2009). Ontology-based tools for the management of customers' portfolios in a deregulated electricity market environment. In: Sicilia, MA., Lytras, M.D. (eds) Metadata and Semantics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-77745-0_26
Download citation
DOI: https://doi.org/10.1007/978-0-387-77745-0_26
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-77744-3
Online ISBN: 978-0-387-77745-0
eBook Packages: Computer ScienceComputer Science (R0)