Conference article

Dymola-JADE Co-Simulation for Agent-Based Control in Office Spaces

Ana Constantin
Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, Germany

Artur Löwen
Institute for Automation of Complex Power Systems, RWTH Aachen University, Germany

Ferdinanda Ponci
Institute for Automation of Complex Power Systems, RWTH Aachen University, Germany

Kristian Huchtemann
Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, Germany

Dirk Müller
Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, Germany

Download articlehttp://dx.doi.org/10.3384/ecp17132345

Published in: Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017

Linköping Electronic Conference Proceedings 132:38, p. 345-351

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Published: 2017-07-04

ISBN: 978-91-7685-575-1

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

This paper presents an application of coupling Modelica under Dymola and JADE to test novel agent-based control for office spaces. The office space with a coupled energy system and weather boundary conditions are modeled in Dymola. The agent platform is programmed in JADE, where the agents communicate with each other to control the technical equipment used to deliver thermal energy to the room. Heating experiments, run for a one room scenario, using a radiator, show better system reaction to the comfort desires of the user when compared to a control with a thermostatic valve, while having similar energy consumption. While the agents run in real time, the simulation in Dymola runs more quickly. We focus on the particularities of the connection for co-simulation to insure smooth transferability of the experiments from simulation to field test, where the energy system as well as the agent platform would be running in real time.

Keywords

agent-based control, JADE, co-simulation

References

Michael Dibley, Haijiang Li, Yacine Rezgui, and John Miles. An ontology framework for intelligent sensor-based building monitoring. Automation in Construction, 28:1–14, 2012. ISSN 09265805. doi: https://doi.org/10.1016/j.autcon.2012.05.018.

ECMA. Ecma-404: The json data interchange format, 10 2013. URL http://www.ecma-international.org/publications/files/ECMA-ST/ECMA-404.pdf.

P.O. Fanger. Thermal Comfort. Danish Technical Press, 1970.

IEA. Building energy performance metrics: Supporting energy efficiency progress in major economies. Technical report, International Energy Agency, 2015a.

IEA. Energy technology perspectives 2015. Technical report, International Energy Agency, 2015b.

T. Labeodan, K Aduda, G. Boxem, and W. Zeiler. On the application of multi-agent systems in buildings for improved building operations, performance and smart grid interaction a survey. Renewable and Sustainable Energy Reviews, 50: 1405–1414, 2015.

Stuart J. Russell and Peter Norvig. Artificial intelligence A modern approach. Prentice Hall/Pearson Education, 2003.

Georg Ferdinand Schneider, Jens Oppermann, Ana Constantin, Rita Streblow, and Dirk Mueller. Hardware-in-the-loopsimulation of a building energy and control system to investigate circulating pump control using modelica. In The 11th International Modelica Conference, 2015.

Olli Seppaenen, William Fisk, and QH Lei. Effect of temperature on task performance in offfice environment. Technical report, Ernest Orlando Lawrence Berkley National Laboraory, 2006.

P. H. Shaikh, N. B. M. Nor, P. Nallagownden, I. Elamvazuthi, and T. Ibrahim. A review on optimized control systems for building energy and comfort management of smart sustainable buildings. Renewable and Sustainable Energy Reviews, 34:409–429, 2014.

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