Achieving national goals of net zero energy buildings requires substantial reduction in the energy consumption of commercial building systems. Although significant progress has been made in the integration of building control systems through the development of standard communication protocols, such as BACnet and BACnet/IP, little progress has been made in making them “intelligent” about optimizing building system-level performance. The focus of this project is to demonstrate the potential for distributed, intelligent software agents to perform this optimization and to develop a research infrastructure suitable for development and testing of advanced agent-base optimization techniques that can improve the energy and comfort performance of building systems.
Objective: To demonstrate the feasibility of intelligent agent control techniques for reducing energy consumption in commercial buildings by optimizing the performance of interacting building systems and to create a research infrastructure suitable for ongoing development and testing of advanced agent based optimization techniques by 2016.
What is the new technical idea? The new technical idea is to adapt advances in intelligent agent technology to solve the control optimization problem. Intelligent agents have been successfully implemented in a variety of applications, including search engines and robotic systems, and a considerable amount of information already exists in the artificial intelligence community on different agent architectures (e.g., deliberating, reactive, and hybrid), agent design and implementation, and agent programming. Intelligent agents know or can learn the performance and status of the systems and equipment they monitor and can communicate and collaborate with other agents to achieve a common goal, such as minimizing energy consumption and/or cost of operation, maximizing comfort, identifying and diagnosing problems, etc. Intelligent agents make it possible to solve the problem of building system optimization in a “distributed manner” which greatly simplifies the computational methods required. Developing intelligent agent technology for this application will require a combination of simulation and prototyping tools along with laboratory facilities utilizing real mechanical systems that can be operated in a reproducible but realistic manner to test agent performance.
What is the research plan? An intelligent building agent simulation program (IBAS) has been developed and used to evaluate some prototype intelligent agents for their suitability to optimize the performance of building systems. The results to date demonstrate that intelligent agents have the potential to solve the optimization problem for building systems and also to be used for automated fault detection and diagnostics. A new laboratory is being constructed that will enable research on intelligent agent control of a mixed system of chillers, thermal storage, and air distribution components under realistic and reproducible operating conditions. The construction of this laboratory will be completed early in FY 2015.
Commissioning the new laboratory will be a major focus in FY 2015. That involves adding instrumentation, programming and verifying control sequences, and testing the data acquisition and archiving system. The laboratory was designed so that different systems can be isolated and tested independently. The performance characteristics of each subsystem will be experimentally determined. The outdoor air unit, which conditions outdoor air to provide the inlet boundary conditions for the laboratory, will be tested to determine the range and reproducibility of inlet conditions that it can provide. Similar tests will be conducted to characterize the performance of the cooling tower simulator, hot water plant, and zone loads. The end result will be a well characterized facility operated using a conventional control strategy.
The other major focus for FY2015 will be completing a software model of the laboratory that will enable rapid evaluation of potential control algorithms. The most promising algorithms can then be deployed in the actual laboratory for evaluation in real systems. Data acquired from laboratory operations will be used to validate the model at both the component and system levels.
An HVACSIM+ model of the laboratory is being developed, but there are several concerns about whether or not HVACSIM+ is the appropriate software tool. In the original version of HVACSIM+, the systems of equations are solved using a method that often fails to converge to a solution, particularly if the initial guess value of a variable is too far from the actual value. This solver was replaced in FY2014 by a more robust solver that, based on limited testing, reliably converges to a solution. The size of the model of the laboratory may also be more than HVACSIM+ can handle. The number of components and equations that need to be solved may be beyond the capabilities of HVACSIM+, so part of building the HVACSIM+ model of the laboratory will be evaluating whether or not HVACSIM+ is capable of being the long term simulation tool for this laboratory and other cyber physical systems.
Research in future years will focus on developing and testing candidate agent based optimization techniques. As promising techniques emerge, the research will be expanded to include field testing that is expected to involve CRADAs with control system manufactures and building owners in order to verify laboratory results and speed commercialization of the technology.
Lessons learned from this research will also enable development of draft specifications for several intelligent building agents (e.g., an Air Handling Unit agent, a Chiller agent), including a list of functions to be included in each agent, technical design features, software architecture, and methods for system identification, communication, and negotiation among agents. NIST will work with standards writing organizations, such as ASHRAE, to develop guidelines and/or standards based on these specifications to facilitate the implementation of intelligent agents in building control applications.
Potential Research Impact:
Improved Energy Efficiency of Operations:
Start Date:October 1, 2011
Lead Organizational Unit:el
Virtual Cybernetic Building Testbed
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