Our buildings are broken. Each year we spend over $400B to power, heat and cool our buildings. Moreover, buildings are the largest source of environmental emissions in the US. As a result, even a modest improvement in energy efficiency of the nation’s building stock would result in substantial economic and environmental benefits. In this project, we focus on driving energy efficiency in commercial buildings because this sector represents a substantial portion of the energy usage and costs within the overall building sector. Enhancing the energy efficiency of commercial buildings is a challenging problem, due to the fact that centralized building systems (HVAC, lighting) must be synthesized and integrated with individual inhabitant behavior and energy consumption patterns (plug-load usage). Our project brings together expertise in computational building science, eco-feedback, network theory, data science and control systems to integrate physical building information and inhabitants with cyber (building-human) interaction models to enable intelligent control of commercial building systems. Specifically, this project will: 1) design an integrated CPS (BI5M) aimed at reducing energy usage in buildings; 2) assess the complex inter-relationships between and across physical building and inhabitant models, cyber building-human interaction and intelligent control models related to energy conservation behavior; and 3) empirically test and validate modules and the overall BI5M system at test-bed buildings on Stanford’s campus and Google’s office park. This research directly addresses the Technology for Cyber-Physical Systems research target area of the CPS program by incorporating measurement (geospatial building data, energy use data), dynamics (inhabitant social networks), and control (enhanced user control of: plug-load devices, HVAC, lighting) into the BI5M system. The BI5M system is centered on the cyber BIM model of the building, and will encompass rigorous systems engineering that will explore relationships across the cyber-physical domains and develop new insights into how the scientific principles of cyber-physical systems can be used to influence the energy efficiency of commercial buildings through both occupant behavior and intelligent control.
This project will tackle the grand challenge of reducing the energy usage of commercial buildings. The educational impacts of this project will extend to participant subjects (students, faculty in the test-bed buildings), as well as a broader student population through the integration of key insights from this work into courses/projects at all three universities. The project team will also disseminate results to practitioners/policy-makers working in building management space through an Outreach Workshop. Lastly, this project will broaden participation in computing fields through a diverse PI team and by partnering with the Girls Who Code nonprofit to integrate project data sets and tools into their activities.