Society at large and DOE in particular have an interest in the continued development and refinement of a smart grid infrastructure that more efficiently and reliably matches electrical resources to demands. While technological advances in recent years have improved the smart grid, these advances have been limited by a lack of granularity of data (e.g. environmental conditions at multiple locations in a space) and control (e.g. ability to control every light in a room independently). This proposal focuses on providing this missing granular data by collecting user-location specific (ULS) data that can be utilized by relevant building systems and ultimately by the smart grid. ULS data can allow for more sophisticated control algorithms for loads (such as lighting and air conditioning) so that total energy use is reduced while individual users receive services (e.g. light levels, temperatures) that better meet their needs. Additionally, when building control systems that rely on ULS data are tied to the smart grid, they can reduce loads when needed (e.g. during peak load events) in a manner that maximizes load shedding while still providing individual users the service levels they need.
