Skip to main content
Log in

Design of a distributed simulation environment for building control applications based on systems engineering methodology

  • Research Article
  • Building Systems and Components
  • Published:
Building Simulation Aims and scope Submit manuscript

Abstract

The analysis of innovative designs that distributes control to buildings over a network is currently a challenging task as exciting building performance simulation tools do not offer sufficient capabilities and the flexibility to fully respond to the full complexity of Automated Buildings (ABs). For that reason, this paper deals with the design and development of a middleware for distributed control and building performance simulations that has been carried out to study and analyze the impact of control systems on building performance applications (i.e., building indoor environments) over a network, rather than costly and time-consuming experiments. The paper also presents a model-based Systems Engineering (SE) methodology for development and design of distributed control and building performance simulations involving two or more different software tools over a network. The main objective of this framework is to run-time couple one or multiple building performance simulation tool(s) with a control modelling environment over a network in order to similarly represent Building Automation and Control Systems (BACS) architecture in a simulation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Ben-Nakhi AE, Mahmoud MA (2002). Energy conservation in buildings through efficient A/C control using neural networks. Applied Energy, 73: 5–23.

    Google Scholar 

  • Blanchard BS (1991). System Engineering Management. New York: John Wiley & Sons.

    Google Scholar 

  • Calvino F, La Gennusa M, Rizzo G, Scaccianoce G (2004). The control of indoor thermal comfort conditions: Introducing a fuzzy adaptive controller. Energy and Buildings, 36: 97–102.

    Google Scholar 

  • Chen K, Jiao Y, Lee ES (2006). Fuzzy adaptive networks in thermal comfort. Applied Mathematics Letters, 19: 420–426.

    Google Scholar 

  • CSTB (2005). Type 155–A new TRNSYS type for coupling TRNSYS and Matlab. Centre Scienfigique et Technique du Bâtiment. Available at http://software.cstb.fr/articles/18.ppt. Accessed 14 Dec 2005.

  • D’Andrea R, Dullerud GE (2003). Distributed control design for spatially interconnected systems. IEEE Transactions on Automatic Control, 48: 1478–1495.

    MathSciNet  MATH  Google Scholar 

  • DSMC (1990). Systems Engineering Management Guide. Proof Copy by Defense Systems Management College, Fort Belvoir, VA, USA.

  • Einarsson B (1995). 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.

    Google Scholar 

  • Ellis PG, Torcellini PA, Crawley DB (2007). Simulation of energy management systems in EnergyPlus. In: Proceedings of the 10th International IBPSA Building Simulation Conference, Beijing, China.

    Google Scholar 

  • ESRU (2002). The ESP-r System for Building Energy Simulation. User Guide Version 10 Series, ESRU Manual U02/1, University of Strathclyde, Scotland, UK

  • Gruber M, Trüschel A, Dalenbäck JO (2014). Model-based controllers for indoor climate control in office buildings—Complexity and performance evaluation. Energy and Buildings, 68: 213–222.

    Google Scholar 

  • INCOSE (2015). International Council on Systems Engineering. Available at http://www.incose.org/. Accessed 14 Jul 2015.

  • ISO (2003). Building Automation and Control Systems (BACS)—Part 5: Data Communication Protocol, ISO Std. 16 484-5.

  • ISO (2004). Building Automation and Control Systems (BACS)—Part 2: Hardware, ISO Std. 16 484-2.

  • Hoang N, Jenkins M, Karangelen N (1996). Data integration for military systems engineering. In: Proceedings of IEEE Symposium & Workshop on Engineering of Computer Based Systems, Friedrichshafen, Germany.

    Google Scholar 

  • Hughes C, Hughes T (2003). Parallel and Distributed Programming using C++. Boston, USA: Addison-Wesley.

    MATH  Google Scholar 

  • Janak M (1997). Coupling building energy and lighting simulation. In: Proceedings of the 5th International IBPSA Building Simulation Conference, Prague, Czech Republic, pp. 307–312.

    Google Scholar 

  • Jelsma J, Kamphuis R, Zeiler W (2003). Learning about smart systems for comfort management and energy use in office buildings. In: Proceedings of ECEEE Summer Study, St Raphael, France.

    Google Scholar 

  • Kamphuis IG, Warmer CJ, Zeiler W, Wortel W, Akkermans JM, Jelsma J (2002). SMART: Experiences with e-services for Smart Buildings. In: Proceedings of ISPLC Conference, Athens, Greece.

    Google Scholar 

  • Kamphuis IG, Warmer CJ, Jong MJM, Wortel W (2005). IIGO: Intelligent Internet mediated control in the built environment: Description of a large-scale experiment in a utility building setting. ECN rapport, ECN-C—05-084, UK.

    Google Scholar 

  • Kalogirou SA, Bojic M (2000). Artificial neural networks for the prediction of the energy consumption of a passive solar building. Energy, 25: 479–491.

    Google Scholar 

  • Kolokotsa D, Niachou K, Geros V, Kalaitzakis K, Stavrakakis GS, Santamouris M (2005). Implementation of an integrated indoor environment and energy management system. Energy and Buildings, 37: 93–99.

    Google Scholar 

  • Kummert M, André P, Nicolas J (2001). Optimal heating control in a passive solar commercial building. Solar Energy, 69: 103–116.

    Google Scholar 

  • Liang J, Du R (2005). Thermal comfort control based on neural network for HVAC application. In: Proceedings of IEEE Conference on Control Applications (CCA 2005), New York, pp. 819–824.

    Google Scholar 

  • Levermore GJ (1992). Building energy management systems: an application to heating and control. London: E & FN SPON, Inc.

    Google Scholar 

  • Loureiro G, Leaney PG, Hodgson M (1999). A systems engineering environment for inte-grated automotive powertrain development. Society for Design and Process Science, USA, vol. 3, pp. 4–41.

    Google Scholar 

  • Lute P, van Paassen D (1995). Optimal indoor temperature control using a predictor. IEEE Control Systems, 15(4): 4–10.

    Google Scholar 

  • Mathers G, Simpson KJ (2000). Framework for the application of systems engineering in the commercial aircraft domain. Report Version 1.2a, American Institute for Aeronautics and Astronautics, USA.

    Google Scholar 

  • Mathews EH, Arndt DC, Piani CB, van Heerden E (2000). Developing cost efficient control strategies to ensure optimal energy use and sufficient indoor comfort. Applied Energy, 66: 135–159.

    Google Scholar 

  • MathWorks (2015). Matlab/Simulink Documentation. Available at http://www.mathworks.com/. Accessed 21 Sep 2015.

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

    Google Scholar 

  • Sahraoui AEK, Buede DM, Sage AP (2008). Systems engineering research. Journal of Systems Science and Systems Engineering, 17: 319–333.

    Google Scholar 

  • Sharples S, Callaghan V, Clarke G (1999). A multi-agent architecture for intelligent building sensing and control. Sensor Review, 19: 135–140.

    Google Scholar 

  • Shishko R (1995). NASA Systems Engineering Handbook. Proof Copy by National Aeronautics and Space Administration, USA.

    Google Scholar 

  • Yahiaoui A, Hensen JLM, Soethout LL (2003). Integration of control and building performance simulation software by run-time coupling. In: Proceedings of the 8th International IBPSA Building Simulation Conference, Eindhoven, the Netherlands, pp. 1435–1441.

    Google Scholar 

  • Yahiaoui A, Hensen JLM, Soethout LL (2004). Developing CORBAbased distributed control and building performance environments by run-time coupling. In: Proceedings of 10th ICCCBE, Weimar, Germany.

    Google Scholar 

  • Yahiaoui A, Hensen JLM, Soethout LL, van Paassen D (2005). Interfacing of control and building performance simulation software with sockets. In: Proceedings of the 9th International IBPSA Building Simulation Conference, Montreal, Canada.

    Google Scholar 

  • Yahiaoui A, Hensen JLM, Soethout LL, van Paassen D (2006a). Model based optimal control for integrated building systems. In: Proceedings of the 6th International Postgraduate Research Conference in the Built and Human Environment, Delf, the Netherlands.

    Google Scholar 

  • Yahiaoui A, Sahraoui AEK, Hensen JLM, Brouwer P (2006b). A Systems Engineering Environment for Integrated Building Design, UK Chapter of INCOSE proceedings, European Systems Engineering Conference, Edinburgh, Scotland, UK

    Google Scholar 

  • Yahiaoui A, Hensen JLM, Soethout LL, van Paassen D (2006c). Simulation based design environment for multi-agent systems in buildings. In: Proceedings of the 7th International Conference on System Simulation in Buildings, Liege, Belgium.

    Google Scholar 

  • Yahiaoui A (2008). A systems engineering approach to embedded control system implementation in buildings. In: Proceedings of the 18th Annual International Symposium of INCOSE, the Netherlands.

    Google Scholar 

  • Yahiaoui A (2013). A systems engineering approach to distributed control and building performance simulation. In: Proceedings of the 29th International Conference of CIB W78, Beirut, Lebanon.

    Google Scholar 

  • Yahiaoui A (2014). A new systematic design approach for distributed control and building performance simulation. Journal of Civil Engineering and Science, 3: 15–25.

    Google Scholar 

  • Yang R, Wang L (2013). Development of multi-agent system for building energy and comfort management based on occupant behaviors. Energy and Buildings, 56: 1–7.

    Google Scholar 

  • Walsh GC, Ye H, Bushnell L (1999). Stability analysis of networked control systems. In: Proceedings of the American Control Conference, Chicago, USA, pp. 2876–2880.

    Google Scholar 

  • Wetter M (2011). Co-simulation of building energy and control systems with the Building Controls Virtual Test Bed. Journal of Building Performance Simulation, 4: 185–203.

    Google Scholar 

  • Wetter M, Zuo W, Nouidui TS, Pang X (2014). Modelica Buildings library. Journal of Building Performance Simulation, 7: 253–270.

    Google Scholar 

  • Wiese P, John P (2002). Engineering design in the multi-discipline era: A systems approach. New York: John Wiley & Sons.

    Google Scholar 

  • Zhai Z (2003). Developing an integrated building design tool by coupling building energy simulation and computational fluid dynamics programs. PhD Dissertation, Massachusetts Institute of Technology, USA.

    Google Scholar 

Download references

Acknowledgements

The author would like to thank Abdelkader Sahraoui, Prof. at LAAS-CNRS of Toulouse in France for his significant support in the application of SE best practices to the development and design of a middleware for distributed control and building performance simulations, and Jan Hensen, Prof. at Eindhoven University of Technology (TU/e) in the Netherlands for his critical help in this research work, as well as the anonymous reviewers for their valuable feedback to the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Azzedine Yahiaoui.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yahiaoui, A. Design of a distributed simulation environment for building control applications based on systems engineering methodology. Build. Simul. 11, 67–85 (2018). https://doi.org/10.1007/s12273-017-0370-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12273-017-0370-3

Keywords

Navigation