Building, energy, and human systems are deeply intertwined in cities. Design decisions regarding buildings impact energy usage and human comfort and productivity. Conversely, human dynamics and associated municipal policy decisions impact the use types of buildings (e.g., residential, commercial, industrial) and drive associated energy consumption patterns. Failing to understand these complex multi- scale interactions between human, building and energy systems leads to sub-optimal design and operating conditions for all three systems and result in significant energy, economic and environmental costs. The overarching goal of this research is to develop an Urban Energy Management Operating System (UrbanEMOS) that integrates methods from engineering, data science, and urban design/policy to understand and optimize building, energy, and human system interactions at and across multiple scales.

By understanding and optimizing the complex interactions between building, energy, and human systems at multiple scales (i.e., building, community, urban) this research aims to provide policy, design, and operational pathways for more sustainable, energy efficient, and productive cities. To accomplish this goal and advance sustainability of the urban built environment, this research will undertake the following integrated research (R) and educational/outreach (E) objectives: R1) Model the dynamics of building and energy systems at multiple scales through integration of machine learning and engineering simulation; R2) Characterize dynamics between building, energy and human systems by developing a graph-based inference model; R3) Model and explore policy, design and operational intervention impacts (energy, economic, environmental); E1) Create a new project-based laboratory course - Data-driven Urban Engineering Lab; E2) Develop K-12/undergraduate internship programs; E3) Launch an online professional training mini-course. Overall, this research is targeted to yield fundamental knowledge on the complex dynamics between building, energy, and human systems and serve as a foundation for life- long integration of scholarly research and education in urban systems engineering to support the design of sustainable, energy efficient, and productive communities.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project Start
Project End
Budget Start
2020-10-01
Budget End
2025-09-30
Support Year
Fiscal Year
2019
Total Cost
$400,000
Indirect Cost
Name
Stanford University
Department
Type
DUNS #
City
Stanford
State
CA
Country
United States
Zip Code
94305