Ontology-based tools for the management of customers' portfolios in a deregulated electricity market environment

  • Nikolaos Tilipakis
  • Christos Douligeris
  • Aristomenis Neris

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.


Demand Response Transmission System Operator Electrical Power Industry Energy Provider Demand Side Management 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    International Energy Agency: Demand Side Bidding for Smaller Customers. Technical report, IEA demand side management programme, (2005)
  2. 2.
    Directive 2003/54/EC of the European Parliament and of the Council of concerning common rules for the internal market in electricity, (2003)
  3. 3.
    European Transmission System Operators: Current state of balance management in South East Europe, June (2006)
  4. 4.
    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)Google Scholar
  5. 5.
    Towards Smart power networks-Lessons learned from European research FP5 projects,
  6. 6.
    Kofod, C.: DR by Danish Domestic Customers using Direct Electric Heating. Technical Report, EU Efflocom project, (2007)
  7. 7.
    OWL Web Ontology Language Reference W3C Recommendation,
  8. 8.
    Radcliffe, Nicholas J.: The Algebra of Genetic Algorithms, Annals of Maths and Artificial Intelligence. Vol 10, 339–384 (1994)MATHCrossRefGoogle Scholar
  9. 9.
    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)Google Scholar
  10. 10.
    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)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of InformaticsUniversity of PiraeusPiraeusGreece
  2. 2.Hellenic Transmission System Operator S.AN. SmyrniGreece

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