As our climate warms, more homes will require air conditioning. Controlling when these air conditioners call for power has enormous implications for balancing supply and demand on our electric grid as more renewables come online.

A team of researchers from the University of Michigan, Los Alamos National Laboratory, UC Berkeley, and Pecan Street Inc. are developing a new way to use algorithmic-based controllers to interpret, aggregate, and respond to air conditioning load across large numbers of homes. This enables slight adjustments to the timing of cooling in individual homes that are unlikely to inconvenience families but promise an efficient and cost-effective way to accommodate fluctuations in power generation from solar and wind.

In this webinar, an expert panel discusses the unique aspects this APRA-E-funded breakthrough research, including algorithm development and how the new hardware and software allows controllers to be demonstrated in the field, as well as explore the commercialization potential of the resulting solution.

The webinar was held June 2, 2022 via Zoom. A recording is available via YouTube, below.

Event Start Date: June 2, 2022 9:30 am

Speakers

Johanna L. Mathieu, University of Michigan

Mathieu is an associate professor of Electrical Engineering and Computer Science with expertise in power systems, control systems, and optimization. Her research develops strategies to coordinate distributed energy resources including flexible loads.

Scott Hinson, Pecan Street Inc.

Hinson is an electrical engineer with deep knowledge of signals and systems. He is the Chief Technology Officer at Pecan Street and directs research efforts to study the grid and climate impacts for integrating renewable technologies, electric vehicles, and software enabled smart devices that will modernize and decarbonize the electric and transportation sectors.

Greg Ledva, Virtual Peaker

Ledva serves as the Director of Emerging Technologies at Virtual Peaker, a company that provides utilities with tools to better manager distributed energy resources. His research spans algorithm development, data analytics, and data science within electric power systems that leverages customer and stakeholder feedback to inform product development decisions.

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