Electricity Markets Ontology to Support MASCEM’s Simulations

  • Gabriel Santos
  • Tiago Pinto
  • Zita Vale
  • Isabel Praça
  • Hugo Morais
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 616)

Abstract

Power systems worldwide are complex and challenging environments. The increasing necessity for an adequate integration of renewable energy sources is resulting in a rising complexity in power systems operation. Multi-agent based simulation platforms have proven to be a good option to study the several issues related to these systems, including the involved players that act in this domain. To take better advantage of these systems, their integration is mandatory. The main contribution of this paper is the development of the Electricity Markets Ontology, which integrates the essential concepts necessary to interpret all the available information related to electricity markets, while enabling an easier cooperation and adequate communication between related systems. Additionally, the concepts and rules defined by this ontology can be extended and complemented according to the needs of other simulation and real systems in this area. Each system’s particular ontology must import the proposed ontology, thus enabling the effective interoperability between independent systems.

Keywords

Electricity markets Multi-agent simulation Ontologies 

References

  1. 1.
    Sioshansi, F.: Evolution of Global Electricity Markets – New paradigms, New Challenges, New Approaches. Academic Press, Waltham (2013)Google Scholar
  2. 2.
    Shahidehpour, M., Yamin, H., Li, Z.: Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management, pp. 233–274. Wiley-IEEE Press, New York (2002)Google Scholar
  3. 3.
    Koritarov, V.: Real-world market representation with agents: modeling the electricity market as a complex adaptive system with an agent-based approach. IEEE Power Energy Mag. 2, 39–46 (2004)CrossRefGoogle Scholar
  4. 4.
    Li, H., Tesfatsion, L.: Development of open source software for power market research: the AMES test bed. J. Energy Markets 2(2), 111–128 (2009)CrossRefGoogle Scholar
  5. 5.
    Migliavacca, G.: SREMS: a short-medium run electricity market simulator based on game theory and incorporating network constraints. IEEE Power Tech, Lausanne, Swiss (2007)Google Scholar
  6. 6.
    Santos, G., et al.: Multi-agent simulation of competitive electricity markets: autonomous systems cooperation for european market modelling. Energy Conv. Manage. 99, 387–399 (2015)CrossRefGoogle Scholar
  7. 7.
    Praça, I., Ramos, C., Vale, Z., Cordeiro, M.: MASCEM: a multi-agent system that simulates competitive electricity markets. IEEE Intell. Syst. 18(6), 54–60 (2003). Special Issue on Agents and MarketsCrossRefGoogle Scholar
  8. 8.
    Pinto, T., Praça, I., Vale, Z., Morais, H., Sousa, T.: Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis. Integr. Comput. Aided Eng. 20(4), 335–346 (2013). IOS PressGoogle Scholar
  9. 9.
    Vale, Z., Pinto, T., Praça, I., Morais, H.: MASCEM - Electricity markets simulation with strategic players. IEEE Intell. Syst. 26(2), 54–60 (2011). Special Issue on AI in Power Systems and Energy MarketsCrossRefGoogle Scholar
  10. 10.
    Foundation for Intelligent Physical Agents (FIPA), FIPA Agent Management Specification (2004). http://fipa.org/specs/fipa00023/. Accessed January 2016
  11. 11.
    Foundation for Intelligent Physical Agents (FIPA), ACL Message Structure Specification (2002). http://www.fipa.org/specs/fipa00061/. Accessed on January 2016
  12. 12.
    Foundation for Intelligent Physical Agents (FIPA), FIPA Ontology Service Specification (2001). http://www.fipa.org/specs/fipa00086/ Accessed on January 2016
  13. 13.
    Catterson, V. et al.: An upper ontology for power engineering applications, April 2010. http://sites.ieee.org/pes-mas/. Accessed on January 2016
  14. 14.
    Alexopoulos, P., Kafentzis, K., Zoumas, C.: ELMO: an interoperability ontology for the electricity market. In: Proceedings of the International Conference on e-Business, Milan, Italy, July 7–10, 2009Google Scholar
  15. 15.
    Dam, K., Chapping, E.: Coupling agent-based models of natural gas and electricity markets. In: Proceedings of the First International Workshop on Agent Technologies for Energy Systems (ATES 2010), pp. 45–52, 11 May 2010Google Scholar
  16. 16.
    Dam, K., Keirstead, J.: Re-use of an ontology for modelling urban energy systems. In: Proceedings of the 3rd International Conference on Infrastructure Systems and Services: Next Generation Infrastructure Systems for Eco-Cities (INFRA), Shenzhen, China, 11–13 November 2010Google Scholar
  17. 17.
    MIBEL - Mercado Ibérico de Electricidade (2016). http://www.mibel.com/. Accessed on January 2016
  18. 18.
    EPEXSPOT - European Power Exchange (2016). https://www.epexspot.com/. Accessed on January 2016
  19. 19.
    Nord Pool Spot (2016). http://www.nordpoolspot.com/. Accessed on January 2016

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Gabriel Santos
    • 1
  • Tiago Pinto
    • 1
  • Zita Vale
    • 1
  • Isabel Praça
    • 1
  • Hugo Morais
    • 2
  1. 1.GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Institute of EngineeringPolytechnic of Porto (ISEP/IPP)PortoPortugal
  2. 2.AUTomation and Control Group – Department of Electrical EngineeringTechnical University of Denmark (DTU)Kongens LyngbyDenmark

Personalised recommendations