NOTE FOR CITRIS 2012 SEED GRANT APPLICANTS: For more information about proposals involving applications of sMAP contact Carl Blumstein (firstname.lastname@example.org)
Today, every aspect of energy networks, from utilities to buildings to process control, operates on its own distinct collection of industry standard and proprietary information silos spanning from physical link to application. This situation frustrates efforts to optimize energy networks as a system, such as matching demand to variable renewable supplies or integrated control involving lighting, environmental conditioning, and occupancy. We have developed and demonstrated a simple universal framework for physical information, sMAP, as a RESTful web service with a natural resource hierarchy and JSON schema-based information representation. sMAP is simple and can naturally absorb the many Smart Grid information silos. Currently, we have over 30,000 active sMAP streams spanning numerous electrical meters (modern IPv6 low-power wireless to legacy modbus to modern smart meters), weather and meteorological streams, ISO market and power availability, steam and water flows, to multiple entire building-wide BACNet installations. Gigabytes of sMAP data are streaming into numerous repository architectures, locally and in the cloud. We are working to harden the sMAP infrastructure and develop the industry proof points, documentation, tutorials, and engineering guides that enable technology transfer, broad industry adoption as a de facto standard, and a rich ecosystem of analysis, modeling, and optimization capabilities. Currently sMAP is being utilized by several research groups in various disciplines across campus and LBNL in projects ranging from whole building energy optimization to understanding miscellaneous electronic plug-loads, from improving occupant comfort to enabling personalized energy management, and to next generation grid design. Building on top of access provided by sMAP, we have been able to quickly develop a personalized lighting control and an HVAC optimization engine which were able to save 40% and 15% in our test building, respectively.
Technical information about sMAP can be found at: http://smap.cs.berkeley.edu.