The advent of net zero buildings and increasingly stringent energy codes for new construction points us in the right direction towards reducing our carbon footprint, but what about the energy performance of the vast numbers of existing buildings? Utilizing advanced control sequences in existing buildings can be a cost-effective way of reducing energy use. Smaller commercial buildings (less than 50,000 square feet (sf)) typically have manually controlled systems (e.g., thermostats and light switches), and traditional controls for large commercial buildings—while typically digital (e.g., Building Automation Systems)— nevertheless use 20-30 year old technology. These systems were designed to be robust and perform simple tasks such as maintaining temperature and pressure setpoints. However, the controls cannot be easily reprogrammed to incorporate new control strategies. Since the controls are proprietary to each vendor, changing the control logic is expensive. A simple change in ventilation rate in each zone of a building may require hours of programming, rendering the task impractical.

In the past few years at UC Berkeley, computer scientists have been developing innovative software tools and platforms. The simple Monitoring and Actuation Profile (sMAP) software provides a consistent interface to data from various sources such as building sensors, networked devices, websites and other programs allowing people to query and use this data to write flexible and extensible control code. The community around this software has steadily grown and now includes new users with domain-specific knowledge (e.g., mechanical engineers and architects) but with limited background in computer science. This paper explores a few examples of how this new community used these tools to write advanced control sequences in real buildings and test innovative energy efficiency algorithms and components.