Innovations in Comfort, Efficiency, and Safety Solutions.
The Building Control Virtual Test
Bed: Improving Building Design and Operations
In today’s complex building design
environment, designers are increasingly using computer modeling to help
them manage calculations, technologies, budgets, and occupant needs.
Using EnergyPlus—the U.S. Department of Energy’s software that simulates energy use in buildings—designers can determine the most energy-efficient use of technologies and designs for the building. Other simulation and modeling platforms and languages accomplish other tasks; for example, the Modelica language can be used to simulate complex engineered systems (such as mechanical, electrical, and control systems), and the MATLAB and Simulink simulation tools can be used for scientific computing (creating algorithms to automate decision making and analyze data to find better ways to design and operate engineered systems).
In 2008, Lawrence Berkeley National Laboratory (Berkeley Lab) developed the Building Controls Virtual Test Bed (BCVTB), which enables these various simulation environments to “talk” to each other. The BCVTB is a software environment that allows expert users to couple simulation programs together virtually, and to couple simulation programs with actual hardware. Based on the Ptolemy II software environment (an open-source modeling and design software developed by the University of California at Berkeley), the BCVTB allows users to expand the capabilities of individual programs by linking them to other programs.
“The BCVTB allows users to test building control systems before they are installed in an actual building,” said Michael Wetter, a BCVTB developer in Berkeley Lab’s Simulation Research Group. “For example, the BCVTB allows users to simulate a building in EnergyPlus and the HVAC and control system in Modelica, while exchanging data between the software programs as they simulate,” he said.
This ability to “co-simulate” gives designers the ability to use models that best accomplish the task needed for each function, rather than trying to modify one model to make it do something it was not specifically designed to do.
According to Wetter, the impetus to develop the BCVTB was to address some of these deficiencies that emerged as researchers and designers used models in more complex and innovative ways. For example, building simulation programs were not designed for multi-disciplinary analysis, and tools were unable to properly analyze innovative systems, control sequences, and equipment not yet included in software packages. When models or tools were not available, designers had to develop them themselves or to rely on expensive and time-intensive full-scale experiments.
The BCVTB overcomes these deficiencies with its co-simulation ability for a variety of software programs:
•The EnergyPlus whole-building energy simulation program
•The Modelica modeling and simulation environment Dymola
•The MATLAB and Simulink tools for scientific computing
•The Radiance ray-tracing software for lighting analysis
•The ESP-r integrated building energy modeling program
•The BACnet stack, which allows data exchange with BACnet-compliant Building Automation Systems (BAS)
•The analog/digital interface USB-1208LS from Measurement Computing Corporation that can be connected to a USB port
Other programs can be used and combined in the BCVTB environment as well.
Typical applications of the BCVTB include:
•Performance assessment of integrated building energy and control
•Development of new control algorithms
•Formal verification of control algorithms prior to their installation in a building—to reduce commissioning time
For example, by combining Modelica with EnergyPlus through the BCVTB, users can model the building heat flow and daylight availability and use Modelica to model innovative building energy and control systems using its “Buildings” library. This allows even more advanced uses of the BCVTB:
•Define on-the-fly new HVAC components and systems in a modular,
hierarchical, object-oriented, equation-based graphical modeling
environment and couple them to EnergyPlus
•Innovate new HVAC system and control architectures for which models do not yet exist in off-the-shelf building simulation programs
•Analyze dynamic effects of HVAC systems, modeled in Modelica, and their local and supervisory control loops, modeled in MATLAB/Simulink, Modelica, or Ptolemy II
•Simulate virtual experiments prior to full-scale testing in a laboratory or a real building to determine the range of required boundary conditions, the type of experiments that need to be conducted and, for example, to improve a control logic in simulation where iterations can be made faster than in an actual experiment.
Real-Time Data Inputs
In addition to coupling software programs
together, the BCVTB can also be used as an interface between the
simulated building and the actual sensors in the physical building.
This approach allows real-time data to pass from the sensors into the
simulated environment and be analyzed against best-case design
scenarios. It can be used in a variety of applications, including
research to improve equipment and controls, as well as in commissioning
buildings once constructed and in operation.
Yao-Jung Wen, senior researcher at Philips Research North America, was one of the first BCVTB users.
“Philips is interested in lighting—what lighting controls can do for energy efficiency and how they interact with other building systems such as blinds or shades, heating or air conditioning,” Wen said. “When we started working with the BCVTB, we wondered, ‘What if we take EnergyPlus out, and plug in a real building?’”
In this scenario, sensors gave Wen’s team actual light levels, which went to the BCVTB interface and were translated into the format that BCVTB recognizes. Then the data were sent to the control algorithm in MATLAB, back to the interface, and then back to the building—moving the blind or shade, for example.
“We used the BCVTB to create a separation between the controls and the physical systems so that the controller could easily be implemented, tested, and tuned with real performance feedback from a physical implementation,” he said.
In another example, the research group at Johnson Controls is working with two universities who are using the BCVTB to couple simulation programs to test the way buildings and HVAC equipment are controlled—with a goal of improving energy efficiency while maintaining comfort.
With McMaster University in Ontario, they are developing and testing a new way to control an air conditioning unit using an advanced control strategy.
“McMaster is coupling an EnergyPlus model of the building with a Modelica model of the HVAC equipment, and is using MATLAB for optimization,” said John House, a principal research engineer with Johnson Controls who is involved with the project. “The BCVTB has been directing the data flow between these various platforms.”
On another project, Johnson Controls worked with the University of Southern California to study how to control building temperatures to minimize the cost of cooling a building.
“Specifically, they were trying to shift cooling loads from the afternoon when electricity was relatively expensive to early morning before occupancy, when the electricity rates were lower. The BCVTB was used to couple an EnergyPlus building model with optimization routines in MATLAB,” House said. The team demonstrated the capability of the control algorithm to shift cooling loads in a Johnson Controls building in Milwaukee, Wisconsin.
“The BCVTB makes us much more efficient—it allows us to use the simulation tools that are best for a particular task,” House said.
This research was funded by the Department of Energy’s Office of Energy Efficiency and Renewable Energy.
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