BRCM Toolbox
What is it?
The Building Resistance-Capacitance Modeling (BRCM) Matlab Toolbox facilitates the physical modeling of buildings for MPC. The Toolbox provides a means for the fast generation of (bi-)linear resistance-capacitance type models from basic geometry, construction and building systems data. Moreover, it supports the generation of the corresponding potentially time-varying costs and constraints. The Toolbox is based on validated modeling principles described in [1].
Features
Generation of a discrete-time bilinear state-space model of the building
Loading from / writing to strictly structured building data files
Visualization of the building
Programmatical parameter manipulation
Providing functions to generate time-varying costs and constraints for the MPC optimization
Simulation of the model
Input data generation from EnergyPlus input data files
Installation
The Toolbox package installer tbxmanager has a broken link which we have not been able to fix. So until further notice a zip archive of the BRCM toolbox is being made available via the following download link: DownloadBRCMToolbox_v1.03.zip (ZIP, 2 MB)vertical_align_bottom. The original tbxmanager installation instructions and links are provided below as they maybe in useful in the installation process.
The BRCM Toolbox is available via tbxmanager, which simplifies the installation and update of freely available Matlab toolboxes.
To install the BRCM Toolbox for the first time, follow these steps in Matlab:
- Install tbxmanager as described on the external pagewebpage.call_made
- Install BRCM by typing:
tbxmanager install brcm
- To check for updates type:
tbxmanager update
Documentation
A BRCM Toolbox Manual is available as a Downloaddownloadable PDF (PDF, 1.2 MB)vertical_align_bottom.
The most detailed description of the modeling methods can be found in the Ph.D. thesis of David Sturzenegger [3].
Copyright and License
The copyright is with the Automatic Control Lab, ETH Zurich.
The Toolbox is licensed under external pageGPLv3call_made If you are interested in a different licensing scheme, please contact the Automatic Control Laboratory.
Contact
If you have any suggestions for improving the toolbox we would be happy to hear from you. Please contact Prof. Roy Smith at the Automatic Control Laboratory, ETH Zurich.
Authors
This toolbox is the work of:
- David Sturzenegger
- Vito Semeraro
- Dimitrios Gyalistras
- Roy S. Smith
References
The Toolbox is described in:
[1] D. Sturzenegger, D. Gyalistras, V. Semeraro, M. Morari, and R. Smith, BRCM Matlab Toolbox: Model Generation for Model Predictive Building Control. American Control Conference, pp. 1063-1069, 2014.
The general modeling concept and the algorithms the Toolbox is based on are described in:
[2] D. Sturzenegger, D. Gyalistras, M. Morari, and R. Smith, Semiautomated modular modeling of buildings for model predictive control. BuildSys’12 Proc. of the Fourth ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, pp. 99–106, 2012.
[3] D. Sturzenegger, Model Predictive Climate Control, Ph.D. thesis, Swiss Federal Institute of Technology (ETH), 2014.
The base building block of the modeling approach is the one-zone model developed in:
[4] Lehmann, Gyalistras, Gwerder, Wirth, Carl. Intermediate complexity model for model predictive control of integrated room automation. Energy and Buildings, vol. 58, pp. 250–262, 2013.
Within the OptiControl-II project (website, report), these algorithms have been used to a create model that was experimentally validated and successfully used over multiple month in the MPC on a real fully operated office building. An analysis of the results of this project are given in:
[5] D. Sturzenegger, D. Gyalistras, M. Morari, and R.S. Smith, Model Predictive Climate Control of a Swiss Office Building: Implementation, Results and Cost-Benefit Analysis, IEEE Trans. Control System Technology, vol. 24, no. 1, pp. 1-12, 2016.