Control Description Language

Michael Wetter
Lawrence Berkeley National Laboratory, Energy Technologies Area, Building Technology and Urban Systems Division, Berkeley, CA, USA

Milica Grahovac
Lawrence Berkeley National Laboratory, Energy Technologies Area, Building Technology and Urban Systems Division, Berkeley, CA, USA

Jianjun Hu
Lawrence Berkeley National Laboratory, Energy Technologies Area, Building Technology and Urban Systems Division, Berkeley, CA, USA

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp1815417

Ingår i: Proceedings of The American Modelica Conference 2018, October 9-10, Somberg Conference Center, Cambridge MA, USA

Linköping Electronic Conference Proceedings 154:2, s. 17-26

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Publicerad: 2019-02-26

ISBN: 978-91-7685-148-7

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


Properly designed and implemented building control sequences can significantly reduce energy consumption. However, there is currently no process with supporting tools that allows the assessment of the performance of different control sequences, export the control sequences in a vendor-neutral format for cost estimation and for implementation on a building automation system through machine-to-machine translation, and reuse the sequences for verification during commissioning.

This paper describes a Control Description Language (CDL) that we developed to create such a process. For CDL, we selected a subset of Modelica that allows a convenient representation of control sequences, simulation of the control sequence coupled to a building energy model, and development of translators from CDL to building automation systems. To aid in the development of such translators, we created a translator from CDL to a JSON intermediate format. In future work, we seek to work with building control providers to develop translators from CDL to commercial building automation systems.

Through a case study, we show that CDL suffices for simulation-based performance assessment of two ASHRAE-published control sequences for a variable air volume flow system of an office building. Moreover, the case study showed that merely due to differences in the control sequences, annual HVAC energy use was reduced by 30%. This difference is larger than the accuracy required when comparing different HVAC systems, thereby questioning the current practice of idealizing control sequences in building energy simulations, and demonstrating the importance of ensuring that the control sequence used during design simulations corresponds to the control sequence that will be implemented in the real building.


controls, buildings, HVAC


ALC, 2018. CtrlSpecBuilder, 2018. URL https://www. ctrlspecbuilder.com.

ASHRAE. ANSI/ASHRAE Standard 135-2004, BACnet, a data communication protocol for building automation and control networks, 2004. ISSN 1041-2336.

ASHRAE. Sequences of Operation for Common HVAC Systems. ASHRAE, Atlanta, GA, 2006.

ASHRAE, 2016. ASHRAE Guideline 36P, High Performance Sequences of Operation for HVAC systems, First Public Review Draft. ASHRAE, June 2016. URL http://gpc36.savemyenergy.com/public-files.

Marco Bonvini and Alberto Leva. A modelica library for industrial control systems. In Proc. of the 9-th Int. Modelica Conf., pages 477–484, Munich, Germany, September 2012. Modelica Association. doi:DOI:10.3384/ecp12076477.

Contemporary Controls, 2017. Sedona Open Control –Reference Manual. Contemporary Controls, September 2017. URL https://www.ccontrols.com/pdf/RM-SEDONA00.pdf.

Michael Deru, Kristin Field, Daniel Studer, Kyle Benne, Brent Griffith, Paul Torcellini, Bing Liu, Mark Halverson, Dave Winiarski, Michael Rosenberg, Mehry Yazdanian, Joe Huang, and Drury Crawley. U.S. Department of Energy commercial reference building models of the national building stock. Technical Report NREL/TP-5500-46861, National Renewables Energy Laboratory, Golden, CO, February 2011.

Nicholas E.P. Fernandez, Srinivas Katipamula, Weimin Wang, YuLong Xie, Mingjie Zhao, and Charles D. Corbin. Impacts of commercial building controls on energy savings and peak load reduction. Technical Report 25985, PNNL, 5 2017.

A. Husaunndee, R. Lahrech, H. Vaezi-Nejad, and J.C. Visier. Simbad: A simulation toolbox for the design and test of HVAC control systems. In Jean Jacques Roux and Monika Woloszyn, editors, Proc. of the 5-th IBPSA Conf., pages 269–276, 1997. URL www.ibpsa.org/proceedings/bs1997/bs97_p022.pdf.

Modelica Association, 2012. Modelica – A Unified Object-Oriented Language for Physical Systems Modeling, Language Specification, Version 3.3. Modelica Association, May 2012. URL https://www.modelica.org/documents/ModelicaSpec33.pdf.

Georg Ferdinand Schneider, Georg Ambrosius Peßler, and Simone Steiger. Modelling and simulation of standardized control functions from building automation. In Proc. of the 12-th Int. Modelica Conf., pages 209–218,

Prague, Czech Republic, may 2017. Modelica Association. doi:DOI:10.3384/ecp17132209.
Siemens, 2000. APOGEE Powers Process Control Language (PPCL) User’s Manual. Siemens Building Technologies, October 2000. URL https://www.quia.com/files/quia/users/hpiracer/AIRC65/PPCL_Users_Manual.

George Thomas. Creating an Open Controller with Sedona FrameworkTM. Contemporary Controls, February 2016. URL https://sedona-alliance.org/pdf/WPSEDONAAA0.pdf.

Michael Wetter, Wangda Zuo, Thierry S. Nouidui, and Xiufeng Pang. Modelica Buildings library. Journal of Building Performance Simulation, 7(4):253–270, 2014. doi:DOI:10.1080/19401493.2013.765506.

Michael Wetter, Jianjun Hu, Milica Grahovac, Brent Eubanks, and Philip Haves. OpenBuildingControl: Modeling feedback control as a step towards formal design, specification, deployment and verification of building control sequences. In To appear in: 2018 Building Performance Modeling Conference and SimBuild, September 2018.

Y. Yang, A. Pinto, A. Sangiovanni-Vincentelli, and Q. Zhu. A design flow for building automation and control systems. In 2010 31st IEEE Real-Time Systems Symposium, pages 105–116, November 2010. doi:10.1109/RTSS.2010.26.

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