Innovative wireless communications, embedded sensors, data analytics, and controls can help meet California's ambitious energy efficiency goals by reducing lighting energy use in commercial buildings. This project developed a suite of networked lighting solutions including the PermaMote, a self-powered sensor and controller for lighting applications. The project also developed the Readings-At-Desk system that integrates sensors with data-driven daylighting control using an open communication interface. To reduce potential confusion for building occupants about operating traditional lighting control systems, the research team created content that could be the basis for a user interface standard for lighting controls. Finally, to help ensure that advanced lighting control systems deliver their promised energy savings, the project team developed a new method for evaluating and specifying lighting system performance.
In the laboratory, these technologies showed lighting energy savings of up to 73 percent for the PermaMote sensor system from occupancy control and daylight dimming features, compared to the same light source (LED replacement lamps) operated via simple on/off scheduling. The project team also developed a proposed standard lighting data model and user interface elements and provided them to the American National Standards Institute Lighting Systems Committee for standardization. To verify performance of lighting systems, the project team developed a more effective metric for capturing the actual energy effect of a lighting system over time—the energy use intensity (kilowatt-hours per square foot per year). The team tested three commercial lighting systems in FLEXLAB® using this new metric, with tests showing a wide range in the accuracy of the self-reported energy-use metric, from 0.5 percent to 28 percent error. The project team estimates that these advanced technologies can reduce California office lighting energy use by 20 percent above normal advanced lighting controls mandated by Title 24 standards, saving about 1,600 gigawatt-hours per year.
Author(s)
Rich Brown, Jordan Shackelford, Anand Prakash, Peter Schwartz, Aditya Khandekar, Srijit Ghosh, Bruce Nordman, Neal Jackson, Erik Page