"From a hardware standpoint, the industry has fulfilled its goal of integrating," says Tom Hartman, principal at The Hartman Co., an engineering firm specializing in smart buildings. "But from a software standpoint, there hasn't been much progress."
By the Numbers
The SFPUC's Green Headquarters
Square footage: 277,500
Height: 13 stories
Construction cost per square foot: $257
Annual energy use: 2.8 million kwh
Renewable energy sources: Solar panels, wind turbines
Maximum energy produced by renewable sources: 227,000 kwh per year
Percent of total energy consumption supplied by renewable power: 7%
Projected overall energy savings versus conventional building: 32%
Expected life of building: 100 years
Projected energy savings over the building's lifetime: $3.7 billion ($500 million in 2012 dollars)
ROI: 26 years
"When it came to pulling all of that data into one platform to streamline management of the building, that wasn't available," Vafaei says. So the commission developed an integrated building management system (IBMS), a custom-built SQL Server database that pulls data from every monitoring and control system, including those that regulate heating and lighting, elevators, generators, solar arrays, the internal window blinds and external shutters that adjust natural lighting, and the roof-mounted weather station. "The IBMS provides a management layer on top of the traditional controls," Vafaei says. The system also aggregates data and provides information dashboards that give an end-to-end view of all systems to building managers, executives, employees and even the public, by way of a 40-foot-wide media wall in the main lobby.
Smart Buildings' Sinopoli worked on the IBMS. "We're at the point now where you can integrate these building systems. An IT infrastructure has really penetrated all building systems," he says. And once the data has been integrated, all of those systems can be functionally connected so that an event in one can trigger a response in another.
At the SFPUC building, for example, the IBMS applies real-time analytics to data from the shade, lighting, HVAC, weather station and room occupancy sensors to determine how shade positioning will affect both cooling and lighting system loads. The shade position is then adjusted automatically.
Not Just for New Construction