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A Practical Approach to Representation of Real-time Building Control Applications in Simulation

  • Azzedine YahiaouiEmail author
Research Article

Abstract

Computer based automation and control systems are becoming increasingly important in smart sustainable buildings, of- ten referred to as automated buildings (ABs), in order to automatically control, optimize and supervise a wide range of building performance applications over a network while minimizing energy consumption and associated green house gas emission. This technology generally refers to building automation and control systems (BACS) architecture. Instead of costly and time-consuming experiments, this paper focuses on development and design of a distributed dynamic simulation environment with the capability to represent BACS architecture in simulation by run-time coupling two or more different software tools over a network. This involves using distributed dynamic simulations as means to analyze the performance and enhance networked real-time control systems in ABs and improve the functions of real BACS technology. The application and capability of this new dynamic simulation environment are demonstrated by an experimental design, in this paper.

Keywords

Distributed dynamic simulation networked control systems building performance applications smart buildings building automation and control systems (BACS) architecture 

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Notes

Acknowledgments

The author would like to thank Pieter Smit, Buurman aan Jeroen Boschlaan van Eindhoven in the Netherlands for his true friendship and continuous encouragement, Professor Abdelkader Sahraoui at LAAS-CNRS of Toulouse in France for his significant support in helping me during these years of hard work, and Professor Jan Hensen at Eindhoven University of Technology (TU/e) in the Netherlands for his critical help in doing this research, as well as the anonymous reviewers for their valuable feedback to the manuscript.

References

  1. [1]
    A. Yahiaoui. A systems engineering approach to distributed control and building performance simulation. In Proceedings of the 29th International Conference of CIB W78, Beirut, Lebanon, pp. 422–431, 2012.Google Scholar
  2. [2]
    A. Yahiaoui, J. Hensen, L. Soethout, D. Van Paassen. Integrating building performance simulation with control modeling using Internet sockets. In Proceedings of the 9th International IBPSA Conference, Montreal, Canada, pp. 1377–1384, 2005.Google Scholar
  3. [3]
    A. Yahiaoui, R. Staal. KR26 A systems engineering approach to embedded control system implementation in buildings. INCOSE International Symposium, vol. 18, no. 1, pp. 1717–1730, 2008. Doi: 10.1002/j.2334–5837.2008. tb00912.x.CrossRefGoogle Scholar
  4. [4]
    M. Janak. Coupling building energy and lighting simulation. In Proceedings of the 5th International IBPSA Conference, Prague, Czech Republic, pp.307–312, 1997.Google Scholar
  5. [5]
    Z. Q. Zhai. Developing An Integrated Building Design Tool by Coupling Building Energy Simulation and Computational Fluid Dynamics Programs, Ph.D. dissertation, MIT, USA, 2003.Google Scholar
  6. [6]
    CSTB. Type 155–A new TRNSYS type for coupling TRNSYS and Matlab, Centre Scienfigique et Technique du Bâtiment, [Online], Available: https://doi.org/www.powershow.com/view/14bc9b-MjlmO/TRNSYSMATLAB_5.powerpoint_ppt_presentation, 2005.
  7. [7]
    M. Wetter. Co–simulation of building energy and control systems with the building controls virtual test bed. Journal of Building Performance Simulation, vol. 4, no. 3, pp. 185–203, 2011. Doi: 10.1080/19401493.2010.518631.CrossRefGoogle Scholar
  8. [8]
    I. Beausoleil–Morrison, F. Macdonald, M. Kummert, T. McDowell, R. Jost. Co–simulation between ESP–r and TRNSYS. Journal of Building Performance Simulation, vol. 7, no. 2, pp. 133–151, 2014. DOI: 10.1080/19401493. 2013.794864.CrossRefGoogle Scholar
  9. [9]
    M. Wetter, W. D. Zuo, S. T. Nouidui, X. F. Pang. Modelica buildings library. Journal of Building Performance Simulation, vol. 7, no. 4, pp. 253–270, 2014. Doi: 10.1080/19401493.2013.765506.CrossRefGoogle Scholar
  10. [10]
    ISO. Building automation and control systems (BACS)–Part 2: Hardware, ISO Std. 16484–2, 2005.Google Scholar
  11. [11]
    ISO. Building automation and control systems (BACS)–Part 5: Data communication protocol, ISO Std. 16484–5, 2014.Google Scholar
  12. [12]
    C. Hughes, T. Hughes. Parallel and Distributed Programming using C++, Boston, USA: Addison–Wesley, 2004.Google Scholar
  13. [13]
    A. Yahiaoui, J. Hensen, L. Soethout. Integration of control and building performance simulation software by runtime coupling. In Proceedings of the 8th International IBPSA Conference and Exhibition, Eindhoven, Netherlands, pp.1435–1441, 2003.Google Scholar
  14. [14]
    A. Yahiaoui, J. L. M. Hensen, L. L. Soethout. Developing CORBA–based distributed control and building performance environments by run–time coupling. In Proceedings of the 10th International Conference on Computing in Civil and Building Engineering, Weimar, Germany, pp. 86–93, 2004.Google Scholar
  15. [15]
    ESRU. The ESP–r System for Building Energy Simulation–User Guide Version 10 Series, E S R U Manual U02/1, University of Strathclyde, Scotland, 2002.Google Scholar
  16. [16]
    B. Einarsson. Mixed language programming, Part 4, mixing ANSI–C with Fortran 77 or Fortran 90. In Proceedings of International Workshop on Current Directions in Numerical Software and High Performance Computing, Kyoto, Japan, 1995.Google Scholar
  17. [17]
    Matlab/Simulink Documentation, (Math Works's website), [Online], Available: https://doi.org/nl.mathworks.com/, 2015.
  18. [18]
    A. Yahiaoui, A. E. K. Sahraoui. A framework for distributed control and building performance simulation. In Proceedings of the 21st International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises, Hammamet, Tunisia, pp. 232–237, 2012. DOI: 10.1109/WETICE.2012.44.Google Scholar
  19. [19]
    W. R. Stevens. UNIX Network Programming, Vol. 2: Interprocess Communications, 2nd ed., Upper Saddle River, USA: Prentice–Hall, 1998.Google Scholar
  20. [20]
    A. Fumagalli, R. Grasso. An efficient asynchronous simulation technique for high speed slotted networks. In Proceeding of the 32nd Annual Simulation Symposium, San Diego, USA, pp. 11–18, 1999. D이: 10.1109/SIMSYM. 1999.766448.CrossRefGoogle Scholar
  21. [21]
    J. Shamsi, C. B. Chu, M. Brockmeyer. Towards partially synchronous overlays: Issues and challenges. In Proceedings of 1st International Workshop on Advanced Architectures and Algorithms for Internet Delivery and Applications, Orlando, USA, pp.10–17, 2005. Doi: 10.1109/AAAIDEA. 2005.17.Google Scholar

Copyright information

© Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Center for Building & SystemsEindhoven University of Technology (TU/e)EindhovenNetherlands

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