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Energy Savings Potential: Identification of self-correctable HVAC system faults showing potential for savings of at least 15% of HVAC unit/system energy consumption. Potential Commercialization Date: 4th Quarter 2012 Contact information: Michael Brambley, 509-375-6875, michael.brambley@pnl.gov Larry Brackney, 303-384-7443, larry.brackney@nrel.gov Demonstration Potential: 5 The demonstration potential for this technology was ranked high based on the need for extensive field testing to prove the validity of the approach to implementing self-correcting HVAC system fault control algorithms. Opportunity #2 - Image Processing Occupancy Sensor Controls Cost-effective, embedded image processing techniques are currently being developed at NREL to address fundamental deficiencies in occupancy sensing technologies, while simultaneously creating entirely new information that may be exploited by BASs for temperature, ventilation, and daylighting control. As the lead laboratory on this project, NREL is responsible for integrating imaging processing algorithm recommendations from ORNL into the embedded system design, performing control demonstrations, and establishing industry partnerships for commercialization of the technology in FY2012. Building occupancy sensing technologies have been readily available for decades; however, the fundamental operating principles have remained unchanged. Performance deficiencies that impact occupant comfort are substantial and generally result in related controls being disabled or severely under-tuned if they are included at all. This two-year project is designed to allow BTP to demonstrate a paradigm shift that eliminates present shortcomings of the technology, creates entirely new information for the next generation of building control, and creates a broader value proposition for building owners through integration of building control with security systems. The first year will result in a demonstration of a cost-effective prototype, while year two will focus on deployment. In FY10, NREL began exploratory work to investigate the state of the art of occupancy sensing and study potential embedded hardware platforms for an image processing approach to occupancy estimation. Preliminary hardware experiments began at the end of FY10 and are based around commercially available, production-like components that support open source software development. A number of tasks are currently underway that will result in a proof-of- concept demonstration of an image processing-based occupancy sensor in FY2012. Applicable DOD Market: All commercial DOD buildings with an emphasis on commercial buildings with operational BASs. 173PDF Image | 4th Annual Chena Renewable Energy Fair
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