SSG: An Ontology-Based Information Model for Smart Grids

  • Khouloud Salameh
  • Richard ChbeirEmail author
  • Haritza Camblong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11360)


Nowadays, an electricity blackout can have a domino effect on the overall power system, causing extremely bad effects on the economical, ecological and operational countries perspectives. All this emphasizes the need for conceiving an upgraded vision of today’s and tomorrow’s power systems that have to be smart to meet the society expectations. Smart grids have been emerging as an appropriate solution for such needs. This work addresses two main related challenges encountered in the management of such power systems: (1) the semantic interoperability needed between their heterogeneous components in order to ensure seamless communication and integration, and (2) a means to consider their various objectives from economical, ecological, and operational perspectives, to mention some. In this paper, we propose a three-layered smart grid management framework, aiming at resolving these two issues. The backbone of the framework is SSG, a generic ontology-based model, detailed here. It aims at modeling the smart grid components, their features and properties, allowing the achievement of the smart grid objectives. Several evaluations have been conducted in order to validate our proposed framework and emphasize the SSG importance and utility in the energy domain. Obtained results are satisfactory and draw several promising perspectives.


Information modeling Ontology Power system Smart grid 


  1. 1.
    Brank, J., Grobelnik, M., Mladenic, D.: A survey of ontology evaluation techniques. In: Proceedings of the Conference on Data Mining and Data Warehouses (SiKDD 2005), pp. 166–170 (2005)Google Scholar
  2. 2.
    Catterson, V.M., Davidson, E.M., McArthur, S.D.: Issues in integrating existing multi-agent systems for power engineering applications. In: Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems, 6-p. IEEE (2005)Google Scholar
  3. 3.
    Cox, W., Considine, T.: Energy, micromarkets, and microgrids. In: Grid-Interop 2011, pp. 1–8 (2011)Google Scholar
  4. 4.
    Cox, W., Holmberg, D., Sturek, D.: OASIS collaborative energy standards, facilities, and ZigBee smart energy. In: Grid-Interop Forum, pp. 1–8 (2011)Google Scholar
  5. 5.
    Cox, W.T., Considine, T., Principal, T.: Architecturally significant interfaces for the smart grid. In: Grid-Interop-The Road to an Interoperable Grid, Denver, Colorado, USA, pp. 17–19 (2009)Google Scholar
  6. 6.
    Dallinger, D., Wietschel, M.: Grid integration of intermittent renewable energy sources using price-responsive plug-in electric vehicles. Renew. Sustain. Energy Rev. 16, 3370–3382 (2012)CrossRefGoogle Scholar
  7. 7.
    BE Design: Facility smart grid information model (2017). Accessed 30 July 2018
  8. 8.
    Fauzey, I.H.M., Nateghi, F., Mohammadi, F., Ismail, F.: Emergent occupational safety & health and environmental issues of demolition work: towards public environment. Procedia-Soc. Behav. Sci. 168, 41–51 (2015)CrossRefGoogle Scholar
  9. 9.
    Gillani, S., Laforest, F., Picard, G.: A generic ontology for prosumer-oriented smart grid. In: EDBT/ICDT Workshops, pp. 134–139 (2014)Google Scholar
  10. 10.
    Gómez-Pérez, A.: Ontology evaluation. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies, pp. 251–273. Springer, Heidelberg (2004). Scholar
  11. 11.
    Goodwin, M., Yazidi, A.: A pattern recognition approach for peak prediction of electrical consumption. Integr. Comput.-Aided Eng. 23, 101–113 (2016)CrossRefGoogle Scholar
  12. 12.
    Grijalva, S., Costley, M., Ainsworth, N.: Prosumer-based control architecture for the future electricity grid. In: 2011 IEEE International Conference on Control Applications (CCA), pp. 43–48. IEEE (2011)Google Scholar
  13. 13.
    Guarino, N.: Formal ontology and information systems. In: Proceedings of FOIS, pp. 81–97. vol. 98 (1998)Google Scholar
  14. 14.
    Hammerstrom, D.J., et al.: Pacific northwest gridwise testbed demonstration projects. Part I. Olympic Peninsula Project, Technical report Pacific Northwest National Laboratory (PNNL), Richland, WA (US) (2007)Google Scholar
  15. 15.
    Hammerstrom, D.J., et al.: Pacific Northwest GridWise\(^{{\rm TM}}\) testbed demonstration projects; Part II. Grid Friendly\(^{{\rm TM}}\) Appliance Project. Technical report Pacific Northwest National Laboratory (PNNL), Richland, WA (US) (2007)Google Scholar
  16. 16.
    Ho, Q.-D., Le-Ngoc, T.: Smart grid communications networks: wireless technologies, protocols, issues and standards. In: Obaidat, M.S., Anpalagan, A., Woungang, I. (eds.) Handbook of Green Information and Communication Systems, pp. 115–146. Academic Press, New York (2012)Google Scholar
  17. 17.
    Kempton, W., Letendre, S.E.: Electric vehicles as a new power source for electric utilities. Transp. Res. Part D: Transp. Environ. 2, 157–175 (1997)CrossRefGoogle Scholar
  18. 18.
    Li, X., Liang, X., Lu, R., Shen, X., Lin, X., Zhu, H.: Securing smart grid: cyber attacks, countermeasures, and challenges. IEEE Commun. Mag. 50(8), 38–45 (2012). ISSN 0163-6804CrossRefGoogle Scholar
  19. 19.
    McMorran, A.W.: An introduction to IEC 61970–301 & 61968–11: The common information model. University of Strathclyde, 93, 124 (2007)Google Scholar
  20. 20.
    Mo, Y., et al.: Cyber-physical security of a smart grid infrastructure. Proc. IEEE 100, 195–209 (2012)CrossRefGoogle Scholar
  21. 21.
    Ritzer, G.: Focusing on the prosumer. In: Blättel-Mink, B., Hellmann, K.U. (eds.) Prosumer Revisited, pp. 61–79. Springer, Cham (2010)CrossRefGoogle Scholar
  22. 22.
    Uschold, M., Gruninger, M.: Ontologies: principles, methods and applications. Knowl. Eng. Rev. 11, 93–136 (1996)CrossRefGoogle Scholar
  23. 23.
    Verhoosel, J., Rumph, F.-J., Konsman, M.: Modeling of flexibility in electricity demand and supply for renewables integration. In: Workshop on eeBuildings Data Models, Sophia Antipolis, France, pp. 1–8 (2011)Google Scholar
  24. 24.
    Wang, C., Liu, H., Wu, F.: The extend CIM for microgrid. In: 2012 China International Conference on Electricity Distribution (CICED), pp. 1–5 (2012).
  25. 25.
    Zowghi, D., Gervasi, V.: The three CS of requirements: consistency, completeness, and correctness. In: International Workshop on Requirements Engineering: Foundations for Software Quality, Essen, Germany: Essener Informatik Beitiage, pp. 155–164 (2002)Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Khouloud Salameh
    • 1
  • Richard Chbeir
    • 2
    Email author
  • Haritza Camblong
    • 3
  1. 1.American University of Ras Al KhaimahRas Al KhaimahUAE
  2. 2.Univ. Pau & Adour Countries, E2S-UPPA, LIUPPA, EA3000AngletFrance
  3. 3.University of the Basque CountryDonostiaSpain

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