Lightweight Learning for the Coordination of Behind-the-meter Resources

Speaker

Yi Wang
The University of Hong Kong.

Title

"Lightweight Learning for the Coordination of Behind-the-meter Resources"

Abstract

The rapid deployment of distributed energy resources (DERs) has fundamentally transformed modern power systems. A large proportion of DERs are situated in houses/buildings, generating/consuming energy behind the smart meters, such as heating, ventilation, and air conditioning systems (HVAC), rooftop photovoltaics(PV), electric vehicles (EV), energy storage systems (ESS), etc. These behind-the-meter (BtM) resources, when effectively coordinated, offer tremendous potential to reduce electricity costs for prosumers and enhance flexibility for power systems.
 

However, the coordination of BtM resources is inherently challenging since they are spatially distributed and temporally varying in nature. This talk introduces our recent research on lightweight learning for the coordination of BtM resources, starting from descriptive analysis for load monitoring, predictive analysis for load
forecasting, and prescriptive analysis for energy management. Our research aims to introduce edge intelligence to ubiquitous edge devices by developing systematic lightweight learning methods to coordinate massive BtM resources efficiently,accurately, and affordably. Several hardware testbeds were established to exemplify the concepts presented.

Our research paves the way for cleaner, more sustainable, and low-carbon power systems by unlocking the potential of BtM resources through advanced edge intelligence.

About Speaker

Yi Wang is currently an Assistant Professor of the Department of Electrical and Electronic Engineering, The University of Hong Kong. He received his Bachelor’s degree from Huazhong University of Science and Technology (HUST) in 2014 and his Ph.D. degree from Tsinghua University in 2019. He was an exchange student researcher at the University of Washington.

From 2019 to 2021, he served as a Postdoctoral Researcher in the Power Systems Laboratory, ETH Zurich. His research interests include Data analytics in the smart grid, energy forecasting, multi-energy systems, Internet-of-things, and cyber-physical-social energy systems. He currently serves as the Secretary of IEEE Customer Systems & Smart Buildings Subcommittee and the Chair of IEEE PES Task Force on Data Sharing in Energy Systems. He also serves as the Associate Editor for IEEE Transactions on Smart Grid and
IEEE Systems Journal. He is the recipient of the 2025 IEEE PES Outstanding Young Engineer Award.