june, 2021

18jun9:00 am1:30 pmMachine Learning for a Resilient, Secure, Carbon-Free Electricity Supply

Event Details

On three consecutive Fridays in June, this workshop will explore three major domains in power systems — dynamics, control, and protection; cybersecurity and privacy; and markets and optimization — and their relationship to capabilities emerging from machine learning and artificial intelligence research to address the aforementioned challenges. Each day of the workshop will focus on one of the three domains by bringing together four experts to give a talk and then take part in a panel discussion that involves answering questions from the audience.

Day 3 (Friday, June 18): Markets, OPF, and Demand Side Response

9:00 am – 9:45 am: Learning and Control of Residential Demand Response, Na Li (Harvard University)

9:45 am – 10:30 am: Learning & Optimization of Distributed Energy Resources: SlrpEV and Hopfield Methods, Scott Moura (University of California, Berkeley)

10:30 am – 10:45 am: Break

10:45 am – 11:30 am: Machine Learning for Optimal Decision Making in Bulk Power Systems Reliability Management, Louis Wehenkel (University of Liege)

11:30 pm – 12:15 pm: Deep Reinforcement Learning for Demand Response in Distribution Networks, Christine Chen (University of British Columbia)

12:15 pm – 12:30pm: Break

12:30 pm – 1:30 pm: Panel Discussion

Zoom Link: https://berkeley.zoom.us/j/99077744047#success


(Friday) 9:00 am - 1:30 pm




Duncan Callaway, Alejandro Domínguez-Garcí, and Marija Ilic