Application of Hybrid Agents to Smart Energy Management of a Prosumer Node
DOI:
https://doi.org/10.9781/ijimai.2013.247Keywords:
Energy, Multi-Agent Systems, Agents, Prosumer Node, HVACAbstract
We outline a solution to the problem of intelligent control of energy consumption of a smart building system by a prosumer planning agent that acts on the base of the knowledge of the system state and of a prediction of future states. Predictions are obtained by using a synthetic model of the system as obtained with a machine learning approach. We present case studies simulations implementing different instantiations of agents that control an air conditioner according to temperature set points dynamically chosen by the user. The agents are able of energy saving while trying to keep indoor temperature within a given comfort interval.Downloads
References
[1] H. Barringer, M. Fisher, D Gabbay, G. Gough, and R. Owens. “Metatem: An introduction. Formal Aspects of Computing”, 7(5): pp. 533–549, 1995.
[2] V. Bevar, S. Costantini, G. De Gasperis, A. Paolucci, and A. Tocchio. "Demonstrator of a multi-agent system for industrial fault detection and repair." Advances on Practical Applications of Agents and MultiAgent Systems. Springer Berlin Heidelberg, 2012. pp. 237-240.
[3] M. K. Chandy, O. Etzion, and R. von Ammon. 10201 Executive Summary and Manifesto – Event Processing. In K. M. Chandy, O. Etzion, and R. von Ammon, editors, Event Processing, number 10201 in Dagstuhl Seminar Proceedings, Dagstuhl, Germany, 2011. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany.
[4] S. Costantini and A. Tocchio “About declarative semantics of logicbased agent languages”. In M. Baldoni and P. Torroni, editors, Declarative Agent Languages and Technologies, LNAI 3229. Springer-Verlag, Berlin, 2006.
[5] S. Costantini and G. De Gasperis. “Complex reactivity with preferences in rule-based agents”. In A. Bikakis and A. Giurca, editors, Rules on the Web: Research and Applications, volume 7438 of Lecture Notes in Computer Science, pp. 167–181. Springer Berlin Heidelberg, 2012.
[6] S. Costantini and A. Tocchio. “A logic programming language for multi-agent systems”. In Logics in Artificial Intelligence, Proc. of the 8th Europ. Conf.,JELIA 2002, LNAI 2424. Springer-Verlag, Berlin, 2002.
[7] S. Costantini and A. Tocchio. “The DALI logic programming agentoriented language”. In Logics in Artificial Intelligence, Proc. of the 9th European Conference, Jelia 2004, LNAI 3229. Springer-Verlag, Berlin, 2004.
[8] S. Costantini and A. Tocchio. “A dialogue games framework for the operational semantics of logic agentoriented languages”. In J. Dix, J o Leite, G. Governatori, and W. Jamroga, editors, Computational Logic in Multi-Agent Systems, 11th International Workshop, CLIMA XI, Proceedings, volume 6245 of Lecture Notes in Computer Science, pp. 238–255. Springer, 2010.
[9] M. Dastani, M. Riemsdijk, and J.J. Meyer. “Programming multi-agent systems in 3apl”. Multi-agent programming, pp. 39–67, 2005.
[10] M. Dastani, F. De Boer, F. Dignum, and J.J. Meyer. “Programming agent deliberation: an approach illustrated using the 3apl language”. In Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 97–104. ACM, 2003.
[11] G. De Gasperis, M. Gimenez De Lorenzo, and F. Muzi. “Intelligence improvement of a prosumer node through the predictive concept”. In Proceedings of The Sith UKSim European Symposium on Computer Modeling and Simulation. IEEE Computer Society, November 2012. Malta.
[12] M. Fisher. “A survey of concurrent metatemthe language and its applications”. Temporal Logic, pp. 480–505, 1994.
[13] M. Fisher. Metatem: The story so far. Programming multi-agent systems, pages 3–22, 2006.
[14] M. Fisher, R. Bordini, B. Hirsch, and P. Torroni. “Computational logics and agents. a roadmap of current technologies and future trends”. Computational Intelligence, 2007.
[15] A. C. Kakas, P. Mancarella, F. Sadri, K. Stathis, and F. Toni. “Computational logic foundations of kgp agents”. J. Artif. Intell. Res. (JAIR), 33: pp. 285–348, 2008.
[16] M. Mulder, J. Treur, and M. Fisher. “Agent modelling in metatem and desire”. Intelligent Agents IV Agent Theories, Architectures, and Languages, pp. 193–207, 1998.
[17] G. Narayanasamy, J. Cecil, and T. Son. “A collaborative framework to realize virtual enterprises using 3apl”. Declarative Agent Languages and Technologies IV, pp. 191–206, 2006.
[18] M. Schmidt , H. Lipson, “Distilling Free-Form Natural Laws from Experimental Data”, Science, Vol. 324, no. 5923, pp. 81 – 85, 2009.
[19] M. Schmidt , H. Lipson, Eureqa (Version 0.99.2 beta) [Software]. Available from http://www.eureqa.com, 2013.
[20] E.H. Mathews, D.C. Arndt , C.B. Piani, E. Heerden. “Developing cost efficient control strategies to ensure optimal energy use and sufficient indoor comfort”. Applied Energy 2000;66:135–59.
[21] A.I. Dounis, C. Caraiscos. Advanced control systems engineering for energy and comfort management in a building environment—A review. Renewable and Sustainable Energy Reviews 13, pp. 1246–1261, 2009.
[22] K. M. Knight, S. A. Klein, and J. A. Duffie. A methodology for the synthesis of hourly weather data. Solar Energy 46.2 pp. 109-120, 1991.
[23] P. Caianiello, S. Costantini, G. De Gasperis, N. Florio, and F. Gobbo. Application of Hybrid Agents to Smart Energy Management of a Prosumer Node. Distributed Computing and Artificial Intelligence. Springer International Publishing, pp 597-607, 2013.
[24] M. Cerullo, G. Fazio, M. Fabbri, F. Muzi, G. Sacerdoti, “Acoustic signal processing to diagnose transiting electric-trains”, IEEE Transactions on Intelligent Transportation Systems, Vol. 6, No. 2 June 2005.
Downloads
Published
-
Abstract17
-
PDF30
Submit Article
Information
