Abstract
A key challenge in the power and energy field is the development of decision-support systems that enable studying big problems as a whole. The interoperability between multi-agent systems that address specific parts of the global problem is essential. Ontologies ease the interoperability between heterogeneous systems providing semantic meaning to the information exchanged between the various parties. The use of ontologies within Smart Grids has been proposed based on the Common Information Model, which defines a common vocabulary describing the basic components used in electricity transportation and distribution. However, these ontologies are focused on utilities’ needs. The development of ontologies that allow the representation of diverse knowledge sources is essential, aiming at supporting the interaction between entities of different natures, facilitating the interoperability between these systems. This paper proposes a set of ontologies to enable the interoperability between different types of agent-based simulators, namely regarding electricity markets, the smart grid, and residential energy management. A case study based on real data shows the advantages of the proposed approach in enabling comprehensive power system simulation studies.
This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 641794 (project DREAM-GO) and grant agreement No. 703689 (project ADAPT). This work has also been supported by National funds by FCT in the scope of Gabriel Santos PhD (SFRH/BD/118487/2016).
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References
Sioshansi, F.P.: Evolution of Global Electricity Markets: New Paradigms, New Challenges, New Approaches (2013)
Ciarreta, A., Espinosa, M.P., Pizarro-Irizar, C.: Has renewable energy induced competitive behavior in the Spanish electricity market? Energy Policy 104, 171–182 (2017)
Geng, Z., Conejo, A.J., Chen, Q., Xia, Q., Kang, C.: Electricity production scheduling under uncertainty: max social welfare vs. min emission vs. max renewable production. Appl. Energy 193, 540–549 (2017)
Santos, G., Pinto, T., Praça, I., Vale, Z.: MASCEM: optimizing the performance of a multi-agent system. Energy 111, 513–524 (2016)
Li, H., Tesfatsion, L.: Development of open source software for power market research: the AMES test bed. J. Energy Mark. 2, 111–128 (2009)
Thimmapuram, P., Veselka, T.D., Koritarov, V., Vilela, S., Pereira, R., Silva, R.F.: Modeling hydro power plants in deregulated electricity markets: integration and application of EMCAS and VALORAGUA. In: 2008 5th International Conference on the European Electricity Market, EEM (2008)
Vale, Z., Pinto, T., Praça, I., Morais, H.: MASCEM: electricity markets simulation with strategic agents. IEEE Intell. Syst. 26, 9–17 (2011)
Oliveira, P., Pinto, T., Morais, H., Vale, Z.: MASGriP a multi-agent smart grid simulation platform. In: IEEE Power and Energy Society General Meeting, pp. 1–8 (2012)
Pinto, T., Vale, Z., Sousa, T.M., Praça, I., Santos, G., Morais, H.: Adaptive learning in agents behaviour: a framework for electricity markets simulation. Integr. Comput. Aided Eng. 21, 399–415 (2014)
Santos, G., Pinto, T., Vale, Z.: Ontologies for the interoperability of heterogeneous multi-agent systems in the scope of power and energy systems. In: De la Prieta, F., et al. (eds.) PAAMS 2017. AISC, vol. 619, pp. 300–301. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-61578-3_42
Gomes, L., Faria, P., Morais, H., Vale, Z., Ramos, C.: Distributed, agent-based intelligent system for demand response program simulation in smart grids. IEEE Intell. Syst. 29, 56–65 (2014)
Faia, R., Pinto, T., Abrishambaf, O., Fernandes, F., Vale, Z., Corchado, J.M.: Case based reasoning with expert system and swarm intelligence to determine energy reduction in buildings energy management. Energy Build. 155, 269–281 (2017)
Teixeira, B., Pinto, T., Silva, F., Santos, G., Praça, I., Vale, Z.: Multi-agent decision support tool to enable interoperability among heterogeneous energy systems (2018)
Fernandes, F., Morais, H., Vale, Z., Ramos, C.: Dynamic load management in a smart home to participate in demand response events. Energy Build. 82, 592–606 (2014). https://doi.org/10.1016/j.enbuild.2014.07.067
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Santos, G., Pinto, T., Vale, Z. (2019). Multi-agent Systems Society for Power and Energy Systems Simulation. In: Davidsson, P., Verhagen, H. (eds) Multi-Agent-Based Simulation XIX. MABS 2018. Lecture Notes in Computer Science(), vol 11463. Springer, Cham. https://doi.org/10.1007/978-3-030-22270-3_10
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