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MLE+: a tool for integrated design and deployment of energy efficient building controls

Published:06 November 2012Publication History

ABSTRACT

We present MLE+, a tool for energy-efficient building automation design, co-simulation and analysis. The tool leverages the high-fidelity building simulation capabilities of EnergyPlus and the scientific computation and design capabilities of Matlab for controller design. MLE+ facilitates integrated building simulation and controller formulation with integrated support for system identification, control design, optimization, simulation analysis and communication between software applications and building equipment. It provides streamlined workflows, a graphical front-end, and debugging support to help control engineers eliminate design and programming errors and take informed decisions early in the design stage, leading to fewer iterations in the building automation development cycle. We show through an example and two case studies how MLE+ can be used for designing energy-efficient control algorithms for both simulated buildings in EnergyPlus and real building equipment via BACnet.

References

  1. D. B. Crawley, L. K. Lawrie, C. O. Pedersen, and F. C. Winkelmann. Energy plus: energy simulation program. ASHRAE journal, 42(4), 2000.Google ScholarGoogle Scholar
  2. SA Klein and University of Wisconsin-Madison Solar Energy Laboratory. TRNSYS: A transient simulation program. Eng. Experiment Station, 1976.Google ScholarGoogle Scholar
  3. P. Strachan. Esp-r: Summary of validation studies. Energy Systems Research Unit, University of Strathclyde, Scotland, UK, 2000.Google ScholarGoogle Scholar
  4. equest: the quick energy simulation tool. http://doe2.com/equest/.Google ScholarGoogle Scholar
  5. F. C. Winkelmann et. al. DOE-2 Supplement: Version 2.1 e. Technical report, Lawrence Berkeley Lab., CA (United States); Hirsch (James J.) and Associates, Camarillo, CA (United States), 1993.Google ScholarGoogle Scholar
  6. A. Tindale. Designbuilder software. Stroud, Gloucestershire, Design-Builder Software Ltd, 2005.Google ScholarGoogle Scholar
  7. EnergyPlus External Interface(s) Application Guide, May 2012.Google ScholarGoogle Scholar
  8. E. F. Camacho and C. Bordons. Model Predictive Control. Springer, 2004.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. G. J. Ward. The RADIANCE lighting simulation and rendering system. In Conf. Computer graphics & interactive techniques. ACM, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. M. A. Piette, G. Ghatikar, S. Kiliccote, E. Koch, D. Hennage, P. Palen-sky, and C. McParland. Open automated demand response communications specification (version 1.0). Technical report, LBNL, 2009.Google ScholarGoogle Scholar
  11. Truong X. Nghiem, M. Behl, Rahul Mangharam, and George J. Pappas. Green scheduling for radiant systems in buildings. In Conference on Decision and Control, Hawaii, USA, Dec. 2012.Google ScholarGoogle ScholarCross RefCross Ref
  12. ASHRAE. Standard 135-1995: BACnet, Data Communication Protocol for Building Automation and Control Networks. ASHRAE, 1995.Google ScholarGoogle Scholar
  13. Steve Karg. Bacnet stack: An open source bacnet protocol stack for embedded systems. http://bacnet.sourceforge.net/.Google ScholarGoogle Scholar
  14. S. Narayanan, J. S. Apte, P. Haves, M. D. Sohn, and J. Elliott. Systems approach to energy efficient building operation. ACEEE Summer Study on Energy Efficiency in Buildings, 2010.Google ScholarGoogle Scholar
  15. Y. Agarwal et. al. Occupancy-driven energy management for smart building automation. In BuildSys, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. V. L. Erickson and A. E. Cerpa. Occupancy based demand response hvac control strategy. In BuildSys, pages 7--12, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. C. Liao, Y. Lin, and P. Barooah. Agent-based and graphical modelling of building occupancy. Journal of Building Performance Simulation, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  18. D. Culler, P. K. Wright, Y. Lu, and M Piette. A distributed intelligent automated demand response building management system. Technical report, University of California, Berkeley, 2011.Google ScholarGoogle Scholar
  19. AWM van Schijndel and JLM Hensen. Integrated heat, air and moisture modeling toolkit in matlab. In Proc. of 9th International IBPSA Conference, 2005.Google ScholarGoogle Scholar
  20. B. P. Rasmussen. Thermosys toolbox user's manual, 2002.Google ScholarGoogle Scholar
  21. Michael Wetter. Co-simulation of building energy and control systems with the building controls virtual test bed. Journal of Building Performance Simulation, 4(3):185--203, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  22. M. Wetter and P. Haves. A modular building controls virtual test bed for the integrations of heterogeneous systems. SimBuild, 2008.Google ScholarGoogle Scholar
  23. Xiufeng Pang, Michael Wetter, Prajesh Bhattacharya, and Philip Haves. A framework for simulation-based real-time whole building performance assessment. Building and Environment, 54(0): 100--108, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  24. C. Sagerschnig, D. Gyalistras, A. Seerig, S. Prívara, J. Cigler, and Z. Vana. Co-simulation for building controller development: The case study of a modern office building. In Proceedings of CISBAT, 2011.Google ScholarGoogle Scholar
  25. K. Ji et. al. Prognostics enabled resilient control for model-based building automation systems. In 12th Building Simulation Conference, 2011.Google ScholarGoogle Scholar
  26. I. Leobner, K. Ponweiser, G. Neugschwandtner, and W. Kastner. Energy efficient production - a holistic modeling approach. In Sustainable Technologies (WCST), 2011 World Congress on, pages 62--67, nov. 2011.Google ScholarGoogle ScholarCross RefCross Ref
  27. F. Sakellariou. Model predictive control for thermally activated building systems. Masters Thesis, 2011.Google ScholarGoogle Scholar
  28. BLOM: The Berkeley Library for Optimization Modeling and Nonlinear Model Predictive Control. http://www.mpc.berkeley.edu/people/sergey-vichik/file/BLOM_paper.pdf.Google ScholarGoogle Scholar

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          • Published in

            cover image ACM Conferences
            BuildSys '12: Proceedings of the Fourth ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings
            November 2012
            227 pages
            ISBN:9781450311700
            DOI:10.1145/2422531

            Copyright © 2012 ACM

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            New York, NY, United States

            Publication History

            • Published: 6 November 2012

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