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Workplace Decarbonization through Real-time Data, Learning and Control

Steven Low
Steven Low

Adam Wierman
Adam Wierman

Lucien Werner
Lucien Werner

Yiheng Xie
Yiheng Xie

Nico Christianson
Nico Christianson

Thuy-Linh Le
Thuy-Linh Le

Christine Ortega
Christine Ortega














PIs: Steven Low and Adam Wierman
Research Team: Lucien Werner, Yiheng Xie, Nicolas Christianson, Thuy-Linh Le, and Christine Ortega
Division of Engineering and Applied Science
Sunlight to Everything Initiative

As uncertainty and volatility increases due to renewable generations, either the grid capacity or renewable curtailment must increase, or both.  This will greatly increase the cost of 24/7 carbon neutrality; e.g., the cost of just the curtailment is estimated at ~$2.7B annually by 2032.  In this project, we will develop technologies that can reduce both the required energy infrastructure and the renewable curtailment.

The key to our solution is the careful exploitation of flexibility in distributed energy resources, such as building loads, large-scale EV charging, and batteries, to adapt to random fluctuations in renewable generations, CO2 intensity and electricity prices.  By equipping workplace energy systems with real-time monitoring, communication, computing and control capabilities, we aim to drastically reduce the capital and operating costs of 24/7 carbon neutrality.  

We will adopt a layered architecture which is not only more scalable, more importantly, it allows each layer to be designed independently, deployed asynchronously, and evolve rapidly, making a complex system more robust to technological changes.  It will enable a much more diverse ecosystem of entrepreneurs and much faster creation and deployment of innovations, ultimately creating a more dynamic and open industry landscape.