Cindy Zhu, Prescriptive Data

Cindy Zhu

Prescriptive Data

Automation and the grid: The rise of grid-interactive, efficient buildings
This keynote address will be delivered virtually.

What is a grid-interactive efficient buildings? What are its characteristics and benefits, and who are its stakeholders? Cindy Zhu will answer these questions and look at how data analytics and machine learning can be applied to demand management and energy optimisation for building owners.

Attendees will learn about using data for automated system optimisation with examples of showcase sites that use edge computing for continuous demand management. The presentation will also look at real-time performance tracking against carbon emissions caps and building energy performance standards.

Data analytics and machine learning can benefit utilities, grid reliability, and grid modernisation through OpenADR, persistent energy efficiency, and transparency of customer end use load profiles. These topics will also be explored in this presentation.

About Cindy Zhu

Cindy Zhu works at the intersection of real estate, energy efficiency, and emerging building technologies. She is Director of the Grid Services team at Prescriptive Data and has previously led major climate and energy initiatives at federal and state government agencies, including the US Department of Energy and the New York State Energy Research and Development Authority. She holds a Bachelor’s Degree in Biological Sciences from Carnegie Mellon University and a Master’s Degree in Environmental Policy and Sustainability Management from The New School.